CN112333479A - E-commerce live broadcast processing method and system based on big data - Google Patents
E-commerce live broadcast processing method and system based on big data Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/44—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs
- H04N21/4408—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs involving video stream encryption, e.g. re-encrypting a decrypted video stream for redistribution in a home network
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- H—ELECTRICITY
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- H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
- H04N21/234—Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs
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Abstract
The disclosed embodiment provides an electronic commerce live broadcast processing method and system based on big data, after acquiring the live broadcast commodity basic information corresponding to the live broadcast commodity target needing commodity object live broadcast video sharing, determining the network security label information matched with the live broadcast commodity basic information, and generates corresponding video transmission protection information according to the network security label information and the network security big data information corresponding to the network security label information, then configuring the transmission control assembly according to the video transmission protection information, then executing the live video sharing of the commodity object, therefore, the corresponding video transmission protection operation can be carried out on the electronic commerce live broadcast terminal through the transmission control component in the commodity object live broadcast video sharing process, and further, the network security in the live broadcast process is improved, and the information loss and tampering of live broadcast content, which may be caused by network security problems, in the commodity live broadcast process are avoided to a certain extent.
Description
Technical Field
The disclosure relates to the technical field of big data and electronic commerce, in particular to a big data-based electronic commerce live broadcast processing method and system.
Background
Electronic commerce generally refers to a novel business operation mode in which, in wide commercial and trade activities worldwide, in an internet environment open to the internet, buyers and sellers conduct various commercial and trade activities without conspiracy based on a browser/server application mode, and consumer online shopping, online transactions and online electronic payments among merchants, and various commercial activities, transaction activities, financial activities, and related comprehensive service activities are realized.
With the rapid development of the internet technology, various live broadcast platforms are continuously developed, and the user can know commodity experience at any time more easily through the commodity live broadcast of electronic commerce. However, the inventor of the present application finds that, in a traditional commercial live broadcast process of electronic commerce, a plurality of network security problems may exist for different commodities, and especially, in the commercial live broadcast process, information of live broadcast content may be lost and tampered due to the network security problems, which may cause a great information security hidden danger.
Disclosure of Invention
In order to overcome the above deficiencies in the prior art at least, an object of the present disclosure is to provide a big data-based e-commerce live broadcast processing method and system, which can configure a transmission control component according to video transmission protection information and then perform live video sharing of a commodity object, so that a corresponding video transmission protection operation can be performed on an e-commerce live broadcast terminal through the transmission control component in a live video sharing process of the commodity object, thereby improving network security in the live broadcast process, and avoiding information loss and falsification of live broadcast content possibly caused by network security problems in the live broadcast process of the commodity to a certain extent.
In a first aspect, the present disclosure provides a big data-based e-commerce live broadcast processing method applied to a network security live broadcast platform, where the network security live broadcast platform is in communication connection with a plurality of e-commerce live broadcast terminals, and the method includes:
after acquiring basic live broadcast commodity information corresponding to a live broadcast commodity target needing commodity object live broadcast video sharing from an e-commerce live broadcast request, determining network security label information matched with the basic live broadcast commodity information, and generating corresponding video transmission protection information according to the network security label information and network security big data information corresponding to the network security label information;
the video transmission protection information is related to a transmission control assembly of a video transmission channel of a live broadcast commodity video stream of the basic information of the live broadcast commodity through an electronic commerce live broadcast plug-in, and after the transmission control assembly is configured according to the video transmission protection information, commodity object live broadcast video sharing is executed;
and carrying out corresponding video transmission protection operation on the electronic commerce live broadcast terminal through the transmission control component in the commodity object live broadcast video sharing process, wherein in the video transmission protection operation process, the transmission control component is continuously updated and configured according to the obtained video transmission protection information through the video transmission channel.
In a possible implementation manner of the first aspect, the step of determining, after obtaining live broadcast commodity basic information corresponding to a live broadcast commodity target that needs to be subjected to live broadcast video sharing of a commodity object from an e-commerce live broadcast request, network security label information that matches the live broadcast commodity basic information includes:
acquiring live broadcast commodity basic information corresponding to a live broadcast commodity target needing commodity object live broadcast video sharing from an e-commerce live broadcast request, wherein the live broadcast commodity basic information comprises a reference network security label, commodity sharing times, a commodity association range and a peripheral commodity range;
determining commodity sharing times/commodity association range values and commodity sharing times/peripheral commodity range values of the basic information of the live commodities;
and determining network security label information matched with the basic information of the live broadcast commodities according to the commodity sharing times/commodity association range value and the commodity sharing times/peripheral commodity range value of the basic information of the live broadcast commodities.
In a possible implementation manner of the first aspect, the step of determining, according to the number of times of commodity sharing/the commodity association range value and the number of times of commodity sharing/the peripheral commodity range value of the live broadcast commodity basic information, network security label information that matches the live broadcast commodity basic information includes:
establishing a network security label matrix according to the commodity sharing times/commodity association range value and the commodity sharing times/peripheral commodity range value of the basic information of the live broadcast commodity, and determining each first network security label corresponding to the basic information of the live broadcast commodity in the network security label matrix according to the commodity sharing times/commodity association range value and the commodity sharing times/peripheral commodity range value of the basic information of the live broadcast commodity;
extracting a vector according to the label characteristic of each reference network security label, and determining the label association range of each reference network security label in the network security label matrix;
determining an initial network security situation value of each reference network security label according to a label association range corresponding to each reference network security label and a corresponding relation between a preset label association range and the initial network security situation value;
for each first network security label included in each reference network security label, determining a target network security posture value of the first network security label according to the initial network security posture value of the reference network security label to which the first network security label belongs;
determining a target commodity association range value, a target commodity sharing number value and a target peripheral commodity range value corresponding to each first network security tag according to the preset commodity sharing number, the preset commodity association range value and the target network security situation value corresponding to each first network security tag;
and determining network security label information matched with the basic information of the live broadcast commodity according to the target commodity sharing number value, the target commodity association range value and the target peripheral commodity range value corresponding to each first network security label, the commodity sharing number in the basic information of the live broadcast commodity, the attack matching data between the commodity association range and the peripheral commodity range, and the relationship between the attack matching data and the preset attack matching data.
In a possible implementation manner of the first aspect, the step of generating corresponding video transmission protection information according to the network security tag information and the network security big data information corresponding to the network security tag information includes:
determining a target network security label with each network security protection frequency degree being greater than a set frequency degree in the network security label information according to the network security big data information corresponding to the network security label information, and a first protection unit and a second protection unit which take the target network security label as protection basic objects, wherein the protection objects of the first protection unit and the second protection unit are not overlapped and have logic association with each other;
determining a vulnerability situation assessment target meeting a first preset condition in the first protection unit, and determining first attack source path information corresponding to the first protection unit according to a data feature vector of attack matching data between network attack behavior information and preset attack verification behavior information of the vulnerability situation assessment target meeting the first preset condition; the vulnerability situation assessment target meeting the first preset condition is a vulnerability situation assessment target of which the network attack behavior information is matched with the preset attack verification behavior information;
determining a vulnerability situation assessment target meeting a second preset condition in the second protection unit, and determining second attack source path information corresponding to the second protection unit according to a data feature vector of attack matching data between network attack behavior information and preset attack verification behavior information of the vulnerability situation assessment target meeting the second preset condition; the vulnerability situation assessment target meeting the second preset condition is a vulnerability situation assessment target of which the network attack behavior information is matched with the preset attack verification behavior information;
obtaining a virtual attack situation linkage value of the vulnerability situation assessment target in each first protection object according to first attack source path information corresponding to the first protection unit, and obtaining a virtual attack situation linkage value of the vulnerability situation assessment target in each second protection object according to second attack source path information in the second protection unit;
respectively carrying out protection simulation test on the vulnerability situation assessment target on each protection object according to the virtual attack situation linkage value of each first protection object and each second protection object to obtain first protection simulation test information of each first protection object and second protection simulation test information of each second protection object;
obtaining corresponding protection simulation test information according to the first protection simulation test information of each first protection object and the second protection simulation test information of each second protection object;
and generating corresponding video transmission protection information according to the protection simulation test information.
In a possible implementation manner of the first aspect, the step of obtaining the corresponding protection simulation test information according to the first protection simulation test information of each first protection object and the second protection simulation test information of each second protection object includes:
determining overlapping protection simulation test information between the first protection simulation test information of each first protection object and the second protection simulation test information of each second protection object;
and determining the overlapping protection simulation test information as the corresponding protection simulation test information.
In a possible implementation manner of the first aspect, the step of generating corresponding video transmission protection information according to the protection simulation test information includes:
aiming at any one simulation test vector in the protection simulation test information, determining a threat degree value and video transmission protection characteristics of the any one simulation test vector, wherein the video transmission protection characteristics of the any one simulation test vector are used for representing protection pre-attribute characteristics and/or protection node characteristics of the any one simulation test vector;
determining the characteristics of video transmission protection parameters according to the threat degree value and the video transmission protection characteristics, configuring the characteristics of global video transmission protection parameters, and determining the vector segmentation parameters of the set vector segments of any simulation test vector according to the characteristics of the video transmission protection parameters and the characteristics of the global video transmission protection parameters;
setting vector segmentation parameters of vector segmentation according to the determined any simulation test vector, and mapping based on the vector segmentation parameters of each vector segmentation of the any simulation test vector to obtain target vector segmentation parameters of each vector segmentation of the any simulation test vector;
iteratively calculating the target vector segmentation parameters of each vector segmentation of any one simulation test vector by continuously adjusting the characteristics of global video transmission protection parameters and based on the characteristics of the video transmission protection parameters until the absolute value of the obtained relative error between the average target vector segmentation parameters of any one simulation test vector and the threat degree value is not higher than a set error value;
and generating corresponding video transmission protection information according to the determined target vector segmentation parameters of each vector segment of each simulation test vector of the protection simulation test information.
In a possible implementation manner of the first aspect, the step of generating corresponding video transmission protection information according to the determined target vector segmentation parameters of each vector segment of each simulation test vector of the protection simulation test information includes:
for each vector segment of each simulation test vector of the protection simulation test information, determining an original test mirror relationship of the vector segment according to a target vector segment parameter of the vector segment; the original test mirror image relationship is used for representing the showing condition of an original test mirror image node occupied by the parameters needing to be tested and mirrored when the vector segmentation parameters and the target vector segmentation parameters are adopted to test the mirror image of the vector segments;
determining a test mirror image value adopted when carrying out positive test mirror image processing on the original test mirror image relationship of each vector segment according to the vector segment parameters of each vector segment, wherein the positive test mirror image processing is used for indicating that the original test mirror image relationship of each vector segment is processed according to an original default mirror image processing mode;
for the original test mirror image relationship of each vector segment, performing positive test mirror image processing on the original test mirror image relationship of the vector segment according to a preset positive test mirror image rule by using the same test mirror image value, and determining the processed positive test mirror image relationship, wherein the positive test mirror image relationship is used for representing the display condition of an upper test mirror image node occupied by parameters needing to be tested and mirrored when the test mirror image value and corresponding target vector segment parameters are used for testing the mirror image of the vector segment;
carrying out test mirror image position conversion on the positive test mirror image relation according to the relevance between upper test mirror image nodes occupied by test mirror image parameters represented by the positive test mirror image relation of each vector section so as to ensure that the relevance between the positive test mirror image relations is lowest;
for each positive test mirror image relationship with the lowest relevance degree, carrying out negative test mirror image processing on the positive test mirror image relationship according to the proportion between the test mirror image value and the vector segmentation parameters of the vector segmentation and a preset negative test mirror image rule, and determining the actual test mirror image relationship after the processing; the actual test mirror image relationship is used for representing the showing condition of an actual test mirror image node occupied by the test mirror image parameter when the vector segmentation parameter of the vector segmentation and the target vector segmentation parameter are adopted for carrying out the test mirror image, wherein the negative test mirror image processing is used for representing that the positive test mirror image relationship of each vector segmentation is processed according to other mirror image processing modes different from the original default mirror image processing mode;
obtaining safety event processing information of each simulation test vector of the protection simulation test information according to the processed actual test mirror image relationship of each vector segment;
and generating corresponding video transmission protection information according to the safety event processing information of each simulation test vector of the protection simulation test information.
In a possible implementation manner of the first aspect, the step of generating corresponding video transmission protection information according to the security event processing information of each simulation test vector of the protection simulation test information includes:
according to the safety event processing information of each simulation test vector of the protection simulation test information, obtaining an event verification node of each safety event in the safety event processing information, and determining a first event verification node array of the safety event processing information;
determining a logic mapping object of the first event check node array and the second event check node array aiming at the second event check node array of each piece of reference test mirror image information stored in the reference test mirror image information list;
regarding the directional reference test mirror image information stored in the reference test mirror image information list, according to a first logic mapping object corresponding to each determined directional reference test mirror image information, taking an object with a maximum logic mapping value in the first logic mapping object as a first target logic mapping object;
aiming at the non-directional reference test mirror image information stored in the reference test mirror image information list, according to a second logic mapping object corresponding to each piece of non-directional reference test mirror image information, taking an object with a maximum logic mapping value in the second logic mapping object as a second target logic mapping object;
comparing a first logic mapping object corresponding to the stored directional reference test mirror image information with a second logic mapping object corresponding to the stored non-directional reference test mirror image information with a first target logic mapping object corresponding to the directional reference test mirror image information and a second target logic mapping object corresponding to the non-directional reference test mirror image information, determining a video transmission protection strategy and logic mapping object reference information of the security event processing information, processing the security event processing information according to the logic mapping object reference information by adopting the video transmission protection strategy, and generating corresponding video transmission protection information.
In a possible implementation manner of the first aspect, the step of associating, by the e-commerce live broadcast plug-in, the video transmission protection information to a transmission control component of a video transmission channel of a live broadcast commodity video stream of the live broadcast commodity basic information, and after configuring the transmission control component according to the video transmission protection information, performing live broadcast video sharing of a commodity object includes:
each video transmission protection unit in the video transmission protection information is associated to a corresponding transmission control node in a transmission control component of a video transmission channel of a live broadcast commodity video stream of the basic information of the live broadcast commodity through an electronic commerce live broadcast plug-in;
and after configuring the video transmission protection configuration information of each video transmission protection unit on the transmission control template of the corresponding transmission control node in the transmission control assembly, executing live video sharing of the commodity object.
In a possible implementation manner of the first aspect, the step of performing, by the transmission control component, a corresponding video transmission protection operation on the e-commerce live broadcast terminal in a live video sharing process of the commodity object includes:
and in the process of sharing the live video of the commodity object, carrying out corresponding video transmission protection operation on the electronic commerce live broadcast terminal through each transmission control node in the transmission control assembly.
In a second aspect, an embodiment of the present disclosure further provides a live processing apparatus of electronic commerce based on big data, which is applied to a network security live platform, where the network security live platform is in communication connection with a plurality of live terminals of electronic commerce, the apparatus includes:
the system comprises a determining module, a live broadcast video sharing module and a display module, wherein the determining module is used for determining network security label information matched with the live broadcast commodity basic information after the live broadcast commodity basic information corresponding to a live broadcast commodity target needing commodity object live broadcast video sharing is obtained from an electronic commerce live broadcast request;
the generating module is used for generating corresponding video transmission protection information according to the network security label information and the network security big data information corresponding to the network security label information;
the association configuration module is used for associating the video transmission protection information to a transmission control assembly of a video transmission channel of a live broadcast commodity video stream of the basic information of the live broadcast commodity through an electronic commerce live broadcast plug-in, configuring the transmission control assembly according to the video transmission protection information and then executing live broadcast video sharing of commodity objects;
and the transmission protection module is used for carrying out corresponding video transmission protection operation on the electronic commerce live broadcast terminal through the transmission control assembly in the commodity object live broadcast video sharing process, wherein in the video transmission protection operation process, the transmission control assembly is continuously updated and configured according to the obtained video transmission protection information through the video transmission channel.
In a third aspect, an embodiment of the present disclosure further provides a big data-based e-commerce live broadcast processing system, where the big data-based e-commerce live broadcast processing system includes a network security live broadcast platform and a plurality of e-commerce live broadcast terminals in communication connection with the network security live broadcast platform;
the network security live broadcast platform is used for determining network security label information matched with the live broadcast commodity basic information after obtaining the live broadcast commodity basic information corresponding to a live broadcast commodity target needing commodity object live broadcast video sharing from an electronic commerce live broadcast request, and generating corresponding video transmission protection information according to the network security label information and network security big data information corresponding to the network security label information;
the network security live broadcast platform is used for associating the video transmission protection information to a transmission control assembly of a video transmission channel of a live broadcast commodity video stream of the basic information of the live broadcast commodity through an electronic commerce live broadcast plug-in, configuring the transmission control assembly according to the video transmission protection information and then executing live broadcast video sharing of commodity objects;
the network security live broadcast platform is used for carrying out corresponding video transmission protection operation on the electronic commerce live broadcast terminal through the transmission control assembly in a commodity object live broadcast video sharing process, wherein in the video transmission protection operation process, the transmission control assembly is continuously updated and configured according to the obtained video transmission protection information through the video transmission channel.
In a fourth aspect, an embodiment of the present disclosure further provides a network security live broadcast platform, where the network security live broadcast platform includes a processor, a machine-readable storage medium, and a network interface, where the machine-readable storage medium, the network interface, and the processor are connected through a bus system, the network interface is used for being in communication connection with at least one e-commerce live broadcast terminal, the machine-readable storage medium is used for storing a program, an instruction, or a code, and the processor is used for executing the program, the instruction, or the code in the machine-readable storage medium, so as to execute the big-data-based e-commerce live broadcast processing method in any one of the first aspect or the possible designs of the first aspect.
In a fifth aspect, an embodiment of the present disclosure provides a computer-readable storage medium, where instructions are stored, and when executed, cause a computer to perform the big data-based e-commerce live broadcast processing method in the first aspect or any one of the possible designs of the first aspect.
Based on any one of the above aspects, the present disclosure determines the network security tag information matching with the live broadcast commodity basic information after obtaining the live broadcast commodity basic information corresponding to the live broadcast commodity target needing commodity object live broadcast video sharing, and generates corresponding video transmission protection information according to the network security label information and the network security big data information corresponding to the network security label information, then configuring the transmission control assembly according to the video transmission protection information, then executing the live video sharing of the commodity object, therefore, the corresponding video transmission protection operation can be carried out on the electronic commerce live broadcast terminal through the transmission control component in the commodity object live broadcast video sharing process, and further, the network security in the live broadcast process is improved, and the information loss and tampering of live broadcast content, which may be caused by network security problems, in the commodity live broadcast process are avoided to a certain extent.
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To more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present disclosure and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings may be obtained from the drawings without inventive effort.
Fig. 1 is a schematic view of an application scenario of a big data-based e-commerce live broadcast processing system according to an embodiment of the present disclosure;
fig. 2 is a schematic flowchart of a big data-based e-commerce live broadcast processing method according to an embodiment of the present disclosure;
fig. 3 is a functional module schematic diagram of a big data-based e-commerce live broadcast processing apparatus according to an embodiment of the present disclosure;
fig. 4 is a block diagram illustrating a structure of a network security live broadcast platform for implementing the big data-based e-commerce live broadcast processing method according to the embodiment of the present disclosure.
Detailed Description
The present disclosure is described in detail below with reference to the drawings, and the specific operation methods in the method embodiments can also be applied to the device embodiments or the system embodiments.
Fig. 1 is an interaction diagram of a big data-based e-commerce live broadcast processing system 10 provided by an embodiment of the present disclosure. The big data-based e-commerce live broadcast processing system 10 can comprise a network security live broadcast platform 100 and an e-commerce live broadcast terminal 200 which is in communication connection with the network security live broadcast platform 100. The big data based e-commerce live broadcast processing system 10 shown in fig. 1 is only one possible example, and in other possible embodiments, the big data based e-commerce live broadcast processing system 10 may also include only one of the components shown in fig. 1 or may also include other components.
In this embodiment, the e-commerce live terminal 200 may include a mobile device, a tablet computer, a laptop computer, or any combination thereof. In some embodiments, the mobile device may include a smart home device, a wearable device, a smart mobile device, a virtual reality device, an augmented reality device, or the like, or any combination thereof. In some embodiments, the smart home devices may include control devices of smart electrical devices, smart monitoring devices, smart televisions, smart cameras, and the like, or any combination thereof. In some embodiments, the wearable device may include a smart bracelet, a smart lace, smart glass, a smart helmet, a smart watch, a smart garment, a smart backpack, a smart accessory, or the like, or any combination thereof. In some embodiments, the smart mobile device may include a smartphone, a personal digital assistant, a gaming device, and the like, or any combination thereof. In some embodiments, the virtual reality device and/or the augmented reality device may include a virtual reality helmet, virtual reality glass, a virtual reality patch, an augmented reality helmet, augmented reality glass, an augmented reality patch, or the like, or any combination thereof. For example, the virtual reality device and/or augmented reality device may include various virtual reality products and the like.
In this embodiment, the network secure live broadcast platform 100 and the e-commerce live broadcast terminal 200 in the big-data-based e-commerce live broadcast processing system 10 may cooperatively execute the big-data-based e-commerce live broadcast processing method described in the following method embodiment, and the detailed description of the method embodiment below may be referred to for the specific steps executed by the network secure live broadcast platform 100 and the e-commerce live broadcast terminal 200.
In order to solve the technical problem in the foregoing background art, fig. 2 is a schematic flow chart of a big data-based e-commerce live broadcast processing method provided in this embodiment of the present disclosure, and the big data-based e-commerce live broadcast processing method provided in this embodiment may be executed by the network security live broadcast platform 100 shown in fig. 1, and the details of the big data-based e-commerce live broadcast processing method are described below.
Step S110, after the live broadcast commodity basic information corresponding to the live broadcast commodity target needing commodity object live broadcast video sharing is obtained from the e-commerce live broadcast request, the network security label information matched with the live broadcast commodity basic information is determined.
And step S120, generating corresponding video transmission protection information according to the network security label information and the network security big data information corresponding to the network security label information.
Step S130, the video transmission protection information is related to a transmission control assembly of a video transmission channel of a live broadcast commodity video stream of the basic information of the live broadcast commodity through the electronic commerce live broadcast plug-in, and after the transmission control assembly is configured according to the video transmission protection information, commodity object live broadcast video sharing is executed.
Step S140, performing corresponding video transmission protection operation on the e-commerce live broadcast terminal 200 through the transmission control component in the process of sharing the live video of the commodity object.
In this embodiment, the live merchandise target may refer to any merchandise that needs to perform electronic commerce, such as but not limited to pregnant women supplies, fast food, cosmetics, electronic products, and the like.
In this embodiment, the network security label information may refer to a network security label that may be associated with basic information of a live broadcast commodity based on a live broadcast commodity target, and the network security label may refer to an access type of network security detection. Correspondingly, the network security big data information may refer to network behavior big data information in a historical access process corresponding to the network security label determined above. The video transmission protection information may refer to configuration information used to generate network security protection during video transmission.
In this embodiment, in the process of performing the video transmission protection operation, the transmission control component may be continuously updated and configured according to the obtained video transmission protection information through the video transmission channel.
Based on the above steps, after the basic information of the live broadcast commodity corresponding to the live broadcast commodity target needing to perform the live broadcast video sharing of the commodity object is obtained, the network security label information matched with the basic information of the live broadcast commodity is determined, and generates corresponding video transmission protection information according to the network security label information and the network security big data information corresponding to the network security label information, then configuring the transmission control assembly according to the video transmission protection information, then executing the live video sharing of the commodity object, therefore, the corresponding video transmission protection operation can be carried out on the electronic commerce live broadcast terminal 200 through the transmission control component in the commodity object live broadcast video sharing process, and further, the network security in the live broadcast process is improved, and the information loss and tampering of live broadcast content, which may be caused by network security problems, in the commodity live broadcast process are avoided to a certain extent.
In a possible implementation manner, step S110 may be specifically implemented by sub-steps, which are described in detail below.
And the substep S111 is used for obtaining the basic information of the live broadcast commodities corresponding to the live broadcast commodity target needing commodity object live broadcast video sharing from the electronic commerce live broadcast request.
For example, the basic information of the live commodities can include a reference network security label, commodity sharing times, commodity association range and peripheral commodity range. In other possible embodiments, the basic information of the live broadcast commodities may further include commodity attribute information of the target of the live broadcast commodities, such as commodity types, commodity adapted groups, commodity marketing time, commodity hot information, and the like. The reference cyber security label may be a preset cyber security label determined according to a history situation, the commodity sharing frequency may be a frequency of sharing the live broadcast commodity target by various channels (e.g., a chat tool, an e-commerce tool, etc.) historically, the commodity association range may be a commodity channel service associated with the live broadcast commodity target, and the peripheral commodity range may be a commodity channel service associated with peripheral commodities of the live broadcast commodity target.
And a substep S112, determining the commodity sharing times/commodity association range value and the commodity sharing times/peripheral commodity range value of the basic information of the live broadcast commodities.
And a substep S113, constructing a network security label matrix according to the commodity sharing times/commodity association range value and the commodity sharing times/peripheral commodity range value of the basic information of the live broadcast commodity, and determining each first network security label corresponding to the basic information of the live broadcast commodity in the network security label matrix according to the commodity sharing times/commodity association range value and the commodity sharing times/peripheral commodity range value of the basic information of the live broadcast commodity.
And a substep S114, extracting a vector according to the label characteristic of each reference network security label, and determining the label association range of each reference network security label in the network security label matrix.
And a substep S115, determining an initial network security situation value of each reference network security label according to the label association range corresponding to each reference network security label and the corresponding relationship between the preset label association range and the initial network security situation value.
And a substep S116, determining, for each first network security label included in each reference network security label, a target network security posture value of the first network security label according to the initial network security posture value of the reference network security label to which the first network security label belongs.
And a substep S117, determining a target commodity association range value, a target commodity sharing number value and a target peripheral commodity range value corresponding to each first network security label according to the preset commodity sharing number, the preset commodity association range value and the target network security situation value corresponding to each first network security label.
And a substep S118, determining network security label information matched with the basic information of the live broadcast commodity according to the target commodity sharing frequency value, the target commodity association range value and the target peripheral commodity range value corresponding to each first network security label, the commodity sharing frequency in the basic information of the live broadcast commodity, the attack matching data between the commodity association range and the peripheral commodity range, and the relationship between the attack matching data and the preset attack matching data.
In a possible implementation manner, step S120 may be specifically implemented by sub-steps, which are described in detail below.
And a substep S121, determining a target network security label with a frequency degree of network security protection greater than a set frequency degree in the network security label information and a first protection unit and a second protection unit which take the target network security label as protection basic objects according to the network security big data information corresponding to the network security label information, wherein the protection objects of the first protection unit and the second protection unit are not overlapped and have logical association with each other.
And a substep S122, determining a vulnerability situation evaluation target meeting a first preset condition in the first protection unit, and determining first attack source path information corresponding to the first protection unit according to a data feature vector of attack matching data between the network attack behavior information of the vulnerability situation evaluation target meeting the first preset condition and preset attack verification behavior information.
For example, the vulnerability situational assessment target meeting the first preset condition may be a vulnerability situational assessment target in which the network attack behavior information matches the preset attack verification behavior information.
And step S123, determining a vulnerability situation evaluation target meeting a second preset condition in the second protection unit, and determining second attack source path information corresponding to the second protection unit according to a data feature vector of attack matching data between the network attack behavior information of the vulnerability situation evaluation target meeting the second preset condition and preset attack verification behavior information.
For example, the vulnerability situational assessment target meeting the second preset condition may be a vulnerability situational assessment target in which the network attack behavior information matches the preset attack verification behavior information.
And a substep S124 of obtaining a virtual attack situation linkage value of the vulnerability situation assessment target in each first protection object according to the first attack source path information corresponding to the first protection unit, and obtaining a virtual attack situation linkage value of the vulnerability situation assessment target in each second protection object according to the second attack source path information in the second protection unit.
And a substep S125, performing protection simulation test on the vulnerability posture assessment target on each protection object respectively according to the virtual attack posture linkage value of each first protection object and each second protection object, and obtaining first protection simulation test information of each first protection object and second protection simulation test information of each second protection object.
And a substep S126, obtaining corresponding protection simulation test information according to the first protection simulation test information of each first protection object and the second protection simulation test information of each second protection object.
And a substep S127 of generating corresponding video transmission protection information according to the protection simulation test information.
As an example, in the sub-step S126, the specific implementation can be further realized in the following embodiments.
(1) Overlapping protection simulation test information between the first protection simulation test information of each first protection object and the second protection simulation test information of each second protection object is determined.
(2) And determining the overlapping protection simulation test information as corresponding protection simulation test information.
As an example, in the sub-step S127, the specific implementation can be further realized in the following embodiments.
(1) And determining the threat degree value and the video transmission protection characteristic of any simulation test vector aiming at any simulation test vector in the protection simulation test information.
For example, video transmission guard features of any of the simulated test vectors may be used to characterize guard pre-attribute features and/or guard node features of any of the simulated test vectors.
(2) Determining the characteristics of video transmission protection parameters according to the threat degree value and the video transmission protection characteristics, configuring the characteristics of global video transmission protection parameters, and determining the vector segmentation parameters of the set vector segments of any simulation test vector according to the characteristics of the video transmission protection parameters and the characteristics of the global video transmission protection parameters.
(3) And setting vector segmentation parameters of vector segmentation according to any determined simulation test vector, and mapping based on the vector segmentation parameters of each vector segmentation of any simulation test vector to obtain target vector segmentation parameters of each vector segmentation of any simulation test vector.
(4) The method comprises the steps of iteratively calculating target vector segmentation parameters of each vector segmentation of any simulation test vector based on the characteristics of the video transmission protection parameters by continuously adjusting the characteristics of global video transmission protection parameters until the absolute value of the relative error between the average target vector segmentation parameters of any simulation test vector and the threat degree value is not higher than a set error value.
(5) And generating corresponding video transmission protection information according to the target vector segmentation parameters of each vector segment of each simulation test vector of the determined protection simulation test information.
For example, for each vector segment of each simulation test vector of the protection simulation test information, the original test mirror relationship of the vector segment may be determined according to the target vector segment parameter of the vector segment. It should be noted that the original test mirror relationship is used to indicate the display condition of the original test mirror node occupied by the parameters to be tested and mirrored when the vector segmentation parameters and the target vector segmentation parameters are used to test the mirror of the vector segment.
On this basis, a test mirror value adopted when the original test mirror relationship of each vector segment is subjected to positive test mirror processing can be determined according to the vector segment parameters of each vector segment, wherein it is worth explaining that the positive test mirror processing is used for indicating that the original test mirror relationship of each vector segment is processed according to an original default mirror processing mode.
And then, for the original test mirror image relationship of each vector segment, performing positive test mirror image processing on the original test mirror image relationship of the vector segment according to a preset positive test mirror image rule by using the same test mirror image value, and determining the processed positive test mirror image relationship.
It should be noted that the positive test mirror image relationship is used to indicate the display condition of the upper test mirror image node occupied by the parameter to be tested mirror image when the test mirror image value and the corresponding target vector segmentation parameter are used to test the mirror image of the vector segment.
Then, according to the relevance between the upper test mirror image nodes occupied by the test mirror image parameters represented by the positive test mirror image relationship of each vector segment, the positive test mirror image relationship is subjected to test mirror image position conversion, so that the relevance between the positive test mirror image relationships is the lowest.
Therefore, for each positive test mirror image relationship with the lowest relevance, negative test mirror image processing is carried out on the positive test mirror image relationship according to the proportion between the test mirror image value and the vector segmentation parameters of the vector segmentation and the preset negative test mirror image rule, and the actual test mirror image relationship after processing is determined. The actual test mirror image relationship is used for representing the showing condition of an actual test mirror image node occupied by the test mirror image parameter when the vector segmentation parameter of the vector segmentation and the target vector segmentation parameter are adopted for carrying out the test mirror image, wherein the negative test mirror image processing is used for representing that the positive test mirror image relationship of each vector segmentation is processed according to other mirror image processing modes different from the original default mirror image processing mode.
Then, the security event processing information of each simulation test vector of the protection simulation test information can be obtained according to the actual test mirror image relationship of each vector segment after processing, and the corresponding video transmission protection information is generated according to the security event processing information of each simulation test vector of the protection simulation test information.
In a possible implementation manner, in the process of generating corresponding video transmission protection information according to the security event processing information of each simulation test vector of the protection simulation test information, this embodiment may specifically obtain an event verification node of each security event in the security event processing information according to the security event processing information of each simulation test vector of the protection simulation test information, and determine the first event verification node array of the security event processing information.
Then, the logical mapping objects of the first event check node array and the second event check node array are determined according to the second event check node array of each piece of reference test mirror information stored in the reference test mirror information list.
And simultaneously, aiming at the directional reference test mirror image information stored in the reference test mirror image information list, according to the first logic mapping object corresponding to each determined directional reference test mirror image information, taking the object with the maximum logic mapping value in the first logic mapping object as a first target logic mapping object.
And simultaneously, aiming at the non-directional reference test mirror image information stored in the reference test mirror image information list, according to a second logic mapping object corresponding to each piece of non-directional reference test mirror image information, taking the object with the maximum logic mapping value in the second logic mapping object as a second target logic mapping object.
Therefore, the first logic mapping object corresponding to the stored directional reference test mirror image information and the second logic mapping object corresponding to the stored non-directional reference test mirror image information can be compared with the first target logic mapping object corresponding to the directional reference test mirror image information and the second target logic mapping object corresponding to the non-directional reference test mirror image information to determine the video transmission protection strategy and the logic mapping object reference information of the security event processing information, and the video transmission protection strategy is adopted to process the security event processing information according to the logic mapping object reference information to generate corresponding video transmission protection information.
In a possible implementation manner, step S130 may be specifically implemented by sub-steps, which are described in detail below.
And a substep S131, associating each video transmission protection unit in the video transmission protection information to a corresponding transmission control node in a transmission control component of a video transmission channel of the live broadcast commodity video stream of the live broadcast commodity basic information through the e-commerce live broadcast plug-in.
And a substep S132, configuring the video transmission protection configuration information of each video transmission protection unit on the transmission control template of the corresponding transmission control node in the transmission control assembly, and then executing commodity object live video sharing.
Therefore, in a possible implementation manner, in step S140, specifically, in the process of sharing live video of a commodity object, each transmission control node in the transmission control component may perform corresponding video transmission protection operation on the e-commerce live broadcast terminal 200.
Fig. 3 is a schematic functional module diagram of a big-data-based e-commerce live broadcast processing apparatus 300 according to an embodiment of the present disclosure, in this embodiment, functional modules of the big-data-based e-commerce live broadcast processing apparatus 300 may be divided according to a method embodiment executed by the network security live broadcast platform 100, that is, the following functional modules corresponding to the big-data-based e-commerce live broadcast processing apparatus 300 may be used to execute various method embodiments executed by the network security live broadcast platform 100. The big data-based e-commerce live broadcast processing apparatus 300 may include a determining module 310, a generating module 320, an association configuration module 330, and a transmission protection module 340, where functions of the functional modules of the big data-based e-commerce live broadcast processing apparatus 300 are described in detail below.
The determining module 310 is configured to determine, after obtaining, from the e-commerce live broadcast request, live broadcast commodity basic information corresponding to a live broadcast commodity target that needs to be subjected to live broadcast video sharing of the commodity object, network security label information that matches the live broadcast commodity basic information. The determining module 310 may be configured to perform the step S110, and the detailed implementation of the determining module 310 may refer to the detailed description of the step S110.
The generating module 320 is configured to generate corresponding video transmission protection information according to the network security tag information and the network security big data information corresponding to the network security tag information. The generating module 320 may be configured to perform the step S120, and the detailed implementation of the generating module 320 may refer to the detailed description of the step S120.
And the association configuration module 330 is configured to associate the video transmission protection information with a transmission control component of a video transmission channel of a live broadcast commodity video stream of the basic information of the live broadcast commodity through the e-commerce live broadcast plug-in, configure the transmission control component according to the video transmission protection information, and perform live broadcast video sharing of the commodity object. The association configuration module 330 may be configured to perform the step S130, and the detailed implementation manner of the association configuration module 330 may refer to the detailed description of the step S130.
And the transmission protection module 340 is configured to perform corresponding video transmission protection operation on the e-commerce live broadcast terminal 200 through the transmission control component in the live video sharing process of the commodity object, wherein in the process of performing the video transmission protection operation, the transmission control component is continuously updated and configured according to the obtained video transmission protection information through the video transmission channel. The transmission guard module 340 may be configured to perform the step S140, and the detailed implementation manner of the transmission guard module 340 may refer to the detailed description of the step S140.
It should be noted that the division of the modules of the above apparatus is only a logical division, and the actual implementation may be wholly or partially integrated into one physical entity, or may be physically separated. And these modules can be realized in the form of software called by processing element; or may be implemented entirely in hardware; and part of the modules can be realized in the form of calling software by the processing element, and part of the modules can be realized in the form of hardware. For example, the determining module 310 may be a processing element separately set up, or may be implemented by being integrated into a chip of the apparatus, or may be stored in a memory of the apparatus in the form of program code, and the function of the determining module 310 may be called and executed by a processing element of the apparatus. Other modules are implemented similarly. In addition, all or part of the modules can be integrated together or can be independently realized. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in the form of software.
For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more microprocessors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), among others. For another example, when some of the above modules are implemented in the form of a processing element scheduler code, the processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor that can call program code. As another example, these modules may be integrated together, implemented in the form of a system-on-a-chip (SOC).
Fig. 4 is a schematic diagram illustrating a hardware structure of the network secure live platform 100 for implementing the control device according to an embodiment of the present disclosure, and as shown in fig. 4, the network secure live platform 100 may include a processor 110, a machine-readable storage medium 120, a bus 130, and a transceiver 140.
In a specific implementation process, at least one processor 110 executes computer-executable instructions stored in the machine-readable storage medium 120 (for example, the determining module 310, the generating module 320, the association configuration module 330, and the transmission guard module 340 included in the big-data-based e-commerce live broadcast processing apparatus 300 shown in fig. 3), so that the processor 110 may execute the big-data-based e-commerce live broadcast processing method according to the above method embodiment, where the processor 110, the machine-readable storage medium 120, and the transceiver 140 are connected through the bus 130, and the processor 110 may be configured to control transceiving actions of the transceiver 140, so as to transceive data with the foregoing e-commerce live broadcast terminal 200.
For a specific implementation process of the processor 110, reference may be made to the above-mentioned method embodiments executed by the network secure live broadcast platform 100, and implementation principles and technical effects thereof are similar, and details of this embodiment are not described herein again.
In the embodiment shown in fig. 4, it should be understood that the Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor, or in a combination of the hardware and software modules within the processor.
The machine-readable storage medium 120 may comprise high-speed RAM memory and may also include non-volatile storage NVM, such as at least one disk memory.
The bus 130 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus 130 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, the buses in the figures of the present application are not limited to only one bus or one type of bus.
In addition, the embodiment of the disclosure also provides a readable storage medium, in which computer execution instructions are stored, and when a processor executes the computer execution instructions, the method for processing the e-commerce live broadcast based on the big data is implemented.
The readable storage medium described above may be implemented by any type of volatile or non-volatile memory device or combination thereof, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk. Readable storage media can be any available media that can be accessed by a general purpose or special purpose computer.
Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present disclosure, and not for limiting the same; while the present disclosure has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present disclosure.
Claims (10)
1. A big data-based e-commerce live broadcast processing method is applied to a network security live broadcast platform, wherein the network security live broadcast platform is in communication connection with a plurality of e-commerce live broadcast terminals, and the method comprises the following steps:
after acquiring basic live broadcast commodity information corresponding to a live broadcast commodity target needing commodity object live broadcast video sharing from an e-commerce live broadcast request, determining network security label information matched with the basic live broadcast commodity information;
generating corresponding video transmission protection information according to the network security label information and network security big data information corresponding to the network security label information;
the video transmission protection information is related to a transmission control assembly of a video transmission channel of a live broadcast commodity video stream of the basic information of the live broadcast commodity through an electronic commerce live broadcast plug-in, and after the transmission control assembly is configured according to the video transmission protection information, commodity object live broadcast video sharing is executed;
carrying out corresponding video transmission protection operation on the electronic commerce live broadcast terminal through the transmission control component in a commodity object live broadcast video sharing process, wherein in the video transmission protection operation process, updating and configuring the transmission control component through the video transmission channel continuously according to the obtained video transmission protection information;
the live broadcast commodity target refers to any commodity needing electronic commerce;
the network security label information refers to a network security label which is possibly associated with basic information of live broadcast commodities based on live broadcast commodity targets, the network security label refers to an access type of network security detection, correspondingly, the network security big data information refers to network behavior big data information in a historical access process corresponding to the network security label determined above, and the video transmission protection information refers to configuration information used for generating network security protection in a video transmission process.
2. The big-data-based e-commerce live broadcast processing method according to claim 1, wherein the step of determining network security label information matched with live broadcast commodity basic information after obtaining live broadcast commodity basic information corresponding to a live broadcast commodity target needing commodity object live broadcast video sharing from an e-commerce live broadcast request comprises:
acquiring live broadcast commodity basic information corresponding to a live broadcast commodity target needing commodity object live broadcast video sharing from an e-commerce live broadcast request, wherein the live broadcast commodity basic information comprises a reference network security label, commodity sharing times, a commodity association range and a peripheral commodity range;
determining commodity sharing times/commodity association range values and commodity sharing times/peripheral commodity range values of the basic information of the live commodities;
and determining network security label information matched with the basic information of the live broadcast commodities according to the commodity sharing times/commodity association range value and the commodity sharing times/peripheral commodity range value of the basic information of the live broadcast commodities.
3. The big data-based e-commerce live broadcast processing method according to claim 1, wherein the step of generating corresponding video transmission protection information according to the cyber security label information and the cyber security big data information corresponding to the cyber security label information includes:
determining a target network security label with each network security protection frequency degree being greater than a set frequency degree in the network security label information according to the network security big data information corresponding to the network security label information, and a first protection unit and a second protection unit which take the target network security label as protection basic objects, wherein the protection objects of the first protection unit and the second protection unit are not overlapped and have logic association with each other;
determining a vulnerability situation assessment target meeting a first preset condition in the first protection unit, and determining first attack source path information corresponding to the first protection unit according to a data feature vector of attack matching data between network attack behavior information and preset attack verification behavior information of the vulnerability situation assessment target meeting the first preset condition; the vulnerability situation assessment target meeting the first preset condition is a vulnerability situation assessment target of which the network attack behavior information is matched with the preset attack verification behavior information;
determining a vulnerability situation assessment target meeting a second preset condition in the second protection unit, and determining second attack source path information corresponding to the second protection unit according to a data feature vector of attack matching data between network attack behavior information and preset attack verification behavior information of the vulnerability situation assessment target meeting the second preset condition; the vulnerability situation assessment target meeting the second preset condition is a vulnerability situation assessment target of which the network attack behavior information is matched with the preset attack verification behavior information;
obtaining a virtual attack situation linkage value of the vulnerability situation assessment target in each first protection object according to first attack source path information corresponding to the first protection unit, and obtaining a virtual attack situation linkage value of the vulnerability situation assessment target in each second protection object according to second attack source path information in the second protection unit;
respectively carrying out protection simulation test on the vulnerability situation assessment target on each protection object according to the virtual attack situation linkage value of each first protection object and each second protection object to obtain first protection simulation test information of each first protection object and second protection simulation test information of each second protection object;
obtaining corresponding protection simulation test information according to the first protection simulation test information of each first protection object and the second protection simulation test information of each second protection object;
and generating corresponding video transmission protection information according to the protection simulation test information.
4. The big-data-based e-commerce live broadcast processing method according to claim 3, wherein the step of obtaining the corresponding protection simulation test information according to the first protection simulation test information of each first protection object and the second protection simulation test information of each second protection object includes:
determining overlapping protection simulation test information between the first protection simulation test information of each first protection object and the second protection simulation test information of each second protection object;
and determining the overlapping protection simulation test information as the corresponding protection simulation test information.
5. The big-data-based e-commerce live broadcast processing method according to claim 3, wherein the step of generating corresponding video transmission protection information according to the protection simulation test information includes:
aiming at any one simulation test vector in the protection simulation test information, determining a threat degree value and video transmission protection characteristics of the any one simulation test vector, wherein the video transmission protection characteristics of the any one simulation test vector are used for representing protection pre-attribute characteristics and/or protection node characteristics of the any one simulation test vector;
determining the characteristics of video transmission protection parameters according to the threat degree value and the video transmission protection characteristics, configuring the characteristics of global video transmission protection parameters, and determining the vector segmentation parameters of the set vector segments of any simulation test vector according to the characteristics of the video transmission protection parameters and the characteristics of the global video transmission protection parameters;
setting vector segmentation parameters of vector segmentation according to the determined any simulation test vector, and mapping based on the vector segmentation parameters of each vector segmentation of the any simulation test vector to obtain target vector segmentation parameters of each vector segmentation of the any simulation test vector;
iteratively calculating the target vector segmentation parameters of each vector segmentation of any one simulation test vector by continuously adjusting the characteristics of global video transmission protection parameters and based on the characteristics of the video transmission protection parameters until the absolute value of the obtained relative error between the average target vector segmentation parameters of any one simulation test vector and the threat degree value is not higher than a set error value;
and generating corresponding video transmission protection information according to the determined target vector segmentation parameters of each vector segment of each simulation test vector of the protection simulation test information.
6. The big-data-based e-commerce live broadcast processing method according to claim 5, wherein the step of generating corresponding video transmission protection information according to the determined target vector segmentation parameters of each vector segment of each simulation test vector of the protection simulation test information includes:
for each vector segment of each simulation test vector of the protection simulation test information, determining an original test mirror relationship of the vector segment according to a target vector segment parameter of the vector segment; the original test mirror image relationship is used for representing the showing condition of an original test mirror image node occupied by the parameters needing to be tested and mirrored when the vector segmentation parameters and the target vector segmentation parameters are adopted to test the mirror image of the vector segments;
determining a test mirror image value adopted when carrying out positive test mirror image processing on the original test mirror image relationship of each vector segment according to the vector segment parameters of each vector segment, wherein the positive test mirror image processing is used for indicating that the original test mirror image relationship of each vector segment is processed according to an original default mirror image processing mode;
for the original test mirror image relationship of each vector segment, performing positive test mirror image processing on the original test mirror image relationship of the vector segment according to a preset positive test mirror image rule by using the same test mirror image value, and determining the processed positive test mirror image relationship, wherein the positive test mirror image relationship is used for representing the display condition of an upper test mirror image node occupied by parameters needing to be tested and mirrored when the test mirror image value and corresponding target vector segment parameters are used for testing the mirror image of the vector segment;
carrying out test mirror image position conversion on the positive test mirror image relation according to the relevance between upper test mirror image nodes occupied by test mirror image parameters represented by the positive test mirror image relation of each vector section so as to ensure that the relevance between the positive test mirror image relations is lowest;
for each positive test mirror image relationship with the lowest relevance degree, carrying out negative test mirror image processing on the positive test mirror image relationship according to the proportion between the test mirror image value and the vector segmentation parameters of the vector segmentation and a preset negative test mirror image rule, and determining the actual test mirror image relationship after the processing; the actual test mirror image relationship is used for representing the showing condition of an actual test mirror image node occupied by the test mirror image parameter when the vector segmentation parameter of the vector segmentation and the target vector segmentation parameter are adopted for carrying out the test mirror image, wherein the negative test mirror image processing is used for representing that the positive test mirror image relationship of each vector segmentation is processed according to other mirror image processing modes different from the original default mirror image processing mode;
obtaining safety event processing information of each simulation test vector of the protection simulation test information according to the processed actual test mirror image relationship of each vector segment;
and generating corresponding video transmission protection information according to the safety event processing information of each simulation test vector of the protection simulation test information.
7. The big-data-based e-commerce live broadcast processing method according to claim 1, wherein the step of generating corresponding video transmission protection information according to the security event processing information of each simulation test vector of the protection simulation test information includes:
according to the safety event processing information of each simulation test vector of the protection simulation test information, obtaining an event verification node of each safety event in the safety event processing information, and determining a first event verification node array of the safety event processing information;
determining a logic mapping object of the first event check node array and the second event check node array aiming at the second event check node array of each piece of reference test mirror image information stored in the reference test mirror image information list;
regarding the directional reference test mirror image information stored in the reference test mirror image information list, according to a first logic mapping object corresponding to each determined directional reference test mirror image information, taking an object with a maximum logic mapping value in the first logic mapping object as a first target logic mapping object;
aiming at the non-directional reference test mirror image information stored in the reference test mirror image information list, according to a second logic mapping object corresponding to each piece of non-directional reference test mirror image information, taking an object with a maximum logic mapping value in the second logic mapping object as a second target logic mapping object;
comparing a first logic mapping object corresponding to the stored directional reference test mirror image information with a second logic mapping object corresponding to the stored non-directional reference test mirror image information with a first target logic mapping object corresponding to the directional reference test mirror image information and a second target logic mapping object corresponding to the non-directional reference test mirror image information, determining a video transmission protection strategy and logic mapping object reference information of the security event processing information, processing the security event processing information according to the logic mapping object reference information by adopting the video transmission protection strategy, and generating corresponding video transmission protection information.
8. The big-data-based e-commerce live broadcast processing method according to claim 1, wherein the step of associating the video transmission protection information to a transmission control component of a video transmission channel of a live broadcast commodity video stream of the live broadcast commodity basic information through an e-commerce live broadcast plug-in, and after configuring the transmission control component according to the video transmission protection information, performing live broadcast video sharing of a commodity object includes:
each video transmission protection unit in the video transmission protection information is associated to a corresponding transmission control node in a transmission control component of a video transmission channel of a live broadcast commodity video stream of the basic information of the live broadcast commodity through an electronic commerce live broadcast plug-in;
and after configuring the video transmission protection configuration information of each video transmission protection unit on the transmission control template of the corresponding transmission control node in the transmission control assembly, executing live video sharing of the commodity object.
9. The big-data-based e-commerce live broadcast processing method according to claim 1, wherein the step of performing corresponding video transmission protection operation on the e-commerce live broadcast terminal through the transmission control component in a commodity object live broadcast video sharing process includes:
and in the process of sharing the live video of the commodity object, carrying out corresponding video transmission protection operation on the electronic commerce live broadcast terminal through each transmission control node in the transmission control assembly.
10. An electronic commerce live broadcast processing system based on big data is characterized by comprising a network security live broadcast platform and a plurality of electronic commerce live broadcast terminals in communication connection with the network security live broadcast platform;
the network security live broadcast platform is used for determining network security label information matched with the live broadcast commodity basic information after obtaining the live broadcast commodity basic information corresponding to a live broadcast commodity target needing commodity object live broadcast video sharing from an electronic commerce live broadcast request, and generating corresponding video transmission protection information according to the network security label information and network security big data information corresponding to the network security label information;
the network security live broadcast platform is used for associating the video transmission protection information to a transmission control assembly of a video transmission channel of a live broadcast commodity video stream of the basic information of the live broadcast commodity through an electronic commerce live broadcast plug-in, configuring the transmission control assembly according to the video transmission protection information and then executing live broadcast video sharing of commodity objects;
the network security live broadcast platform is used for carrying out corresponding video transmission protection operation on the electronic commerce live broadcast terminal through the transmission control component in a commodity object live broadcast video sharing process, wherein in the video transmission protection operation process, the transmission control component is continuously updated and configured according to the obtained video transmission protection information through the video transmission channel;
the live broadcast commodity target refers to any commodity needing electronic commerce;
the network security label information refers to a network security label which is possibly associated with basic information of live broadcast commodities based on live broadcast commodity targets, the network security label refers to an access type of network security detection, correspondingly, the network security big data information refers to network behavior big data information in a historical access process corresponding to the network security label determined above, and the video transmission protection information refers to configuration information used for generating network security protection in a video transmission process.
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CN202011211997.7A CN112333479A (en) | 2020-04-30 | 2020-04-30 | E-commerce live broadcast processing method and system based on big data |
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CN202011211997.7A CN112333479A (en) | 2020-04-30 | 2020-04-30 | E-commerce live broadcast processing method and system based on big data |
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CN111626816B (en) * | 2020-05-10 | 2021-02-02 | 上海星地通讯工程研究所 | Image interaction information processing method based on e-commerce live broadcast and cloud computing platform |
CN113613062B (en) * | 2021-07-08 | 2024-01-23 | 广州云智达创科技有限公司 | Video data processing method, device, equipment and storage medium |
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CN103123707A (en) * | 2011-11-18 | 2013-05-29 | 苏州中茵泰格科技有限公司 | Credit card safety payment method and system based on Internet Protocol Television (IPTV) |
CN106548352A (en) * | 2016-08-24 | 2017-03-29 | 南通芯电物联网科技有限责任公司 | A kind of commodity counterfeit prevention traceability system and its implementation |
CN107424041A (en) * | 2017-05-25 | 2017-12-01 | 周睿 | Agricultural product coproduction is distributed and joint exhibiting and marketing electric business platform |
CN109039991A (en) * | 2017-06-08 | 2018-12-18 | 也买(上海)商贸有限公司 | A kind of network buys the encryption method of wine system and its encrypting module |
CN108777688A (en) * | 2018-06-07 | 2018-11-09 | 中国联合网络通信集团有限公司 | Video security monitoring method and system |
CN109640110A (en) * | 2018-09-21 | 2019-04-16 | 河南金路网络科技有限公司 | On a kind of line of shopping platform with the video interactive method under line |
CN109446817A (en) * | 2018-10-29 | 2019-03-08 | 成都思维世纪科技有限责任公司 | A kind of detection of big data and auditing system |
CN109559113A (en) * | 2018-12-19 | 2019-04-02 | 深圳市力量威科技有限公司 | A kind of transaction system without network communication |
CN111757130A (en) * | 2019-06-27 | 2020-10-09 | 上海妃鱼网络科技有限公司 | Broadcast selection method and system for Internet live broadcast |
CN110445807A (en) * | 2019-08-23 | 2019-11-12 | 瑞森网安(福建)信息科技有限公司 | Network security situation sensing system and method |
CN111681135B (en) * | 2020-08-17 | 2021-03-09 | 北京德润良品健康科技有限公司 | Personalized customized central kitchen capable of accurately tracing to source and management method thereof |
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