CN116720202B - Service information detection method, device, electronic equipment and computer readable medium - Google Patents
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Abstract
The embodiment of the disclosure discloses a service information detection method, a service information detection device, electronic equipment and a computer readable medium. One embodiment of the method comprises the following steps: classifying the service information set of the supply end to generate a first service information set of the supply end and a second service information set of the supply end; performing complement processing on each first supply end service information to generate complement supply end service information; combining the second supply end service information group and the complement supply end service information to form a supply end service information set to be detected; detecting the service information of the supply end to be detected to generate a detection result; marking the service information of the supply end to be detected according to the detection result to generate the service information of the supply end to be detected; and carrying out encryption processing on each detection supply terminal service information to generate encryption supply terminal service information, and obtaining an encryption supply terminal service information set. The embodiment shortens the service information detection time and quickens the data circulation time.
Description
Technical Field
Embodiments of the present disclosure relate to the field of computer technology, and in particular, to a service information detection method, apparatus, electronic device, and computer readable medium.
Background
When the statistical analysis is performed on the service data, each service data needs to be detected in advance due to more owned data. Currently, the detection of service data of each party is generally performed by the following modes: and detecting the business data of each party one by business personnel.
However, the following technical problems generally exist in the above manner:
firstly, more service data, easy missing data in manual detection, longer detection time and delayed data circulation time;
secondly, due to certain sensitivity of the service data, the service data of each party is detected one by service personnel, so that the data leakage is easy to cause;
thirdly, the manual detection efficiency is lower, and the detection angle is single, so that abnormal data are easy to flow out.
The above information disclosed in this background section is only for enhancement of understanding of the background of the inventive concept and, therefore, may contain information that does not form the prior art that is already known to those of ordinary skill in the art in this country.
Disclosure of Invention
The disclosure is in part intended to introduce concepts in a simplified form that are further described below in the detailed description. The disclosure is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
Some embodiments of the present disclosure propose a business information detection method, apparatus, electronic device, and computer readable medium to solve one or more of the technical problems mentioned in the background section above.
In a first aspect, some embodiments of the present disclosure provide a service information detection method, including: acquiring a supply end service information set corresponding to a target service terminal in a preset time period, wherein the supply end service information in the supply end service information set corresponds to a supply end, and the supply end service information in the supply end service information set comprises: auditing duration, service order quantity, delivery time rate and quality sampling qualification rate; classifying the service information sets of the supply end to generate a first service information set of the supply end and a second service information set of the supply end; performing completion processing on each first supply end service information in the first supply end service information group to generate completion supply end service information, and obtaining a completion supply end service information group; combining the second supply end service information group and the complement supply end service information group into a supply end service information set to be detected; for each to-be-detected supply end service information in the to-be-detected supply end service information set, executing the following processing steps: detecting the service information of the to-be-detected supply end to generate a detection result; marking the service information of the to-be-detected supply end according to the detection result to generate service information of the detection supply end; and carrying out encryption processing on each generated detection supply terminal service information to generate encryption supply terminal service information, obtaining an encryption supply terminal service information set, and storing the encryption supply terminal service information set into a target database.
In a second aspect, some embodiments of the present disclosure provide a service information detection apparatus, including: the system comprises an acquisition unit configured to acquire a supply end service information set corresponding to a target service terminal in a preset time period, wherein the supply end service information in the supply end service information set corresponds to a supply end, and the supply end service information in the supply end service information set comprises: auditing duration, service order quantity, delivery time rate and quality sampling qualification rate; the classification unit is configured to perform classification processing on the service information set of the supply end so as to generate a first service information set of the supply end and a second service information set of the supply end; the completion unit is configured to perform completion processing on each first supply end service information in the first supply end service information group so as to generate completion supply end service information and obtain a completion supply end service information group; a combining unit configured to combine the second supply-side service information set and the complementary supply-side service information set into a supply-side service information set to be detected; the detection unit is configured to execute the following processing steps for each to-be-detected supply end service information in the to-be-detected supply end service information set: detecting the service information of the to-be-detected supply end to generate a detection result; marking the service information of the to-be-detected supply end according to the detection result to generate service information of the detection supply end; and the encryption unit is configured to encrypt each generated detection supply terminal service information to generate encryption supply terminal service information, obtain an encryption supply terminal service information set and store the encryption supply terminal service information set into the target database.
In a third aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; a storage device having one or more programs stored thereon, which when executed by one or more processors causes the one or more processors to implement the method described in any of the implementations of the first aspect above.
In a fourth aspect, some embodiments of the present disclosure provide a computer readable medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method described in any of the implementations of the first aspect above.
The above embodiments of the present disclosure have the following advantageous effects: by the service information detection method of some embodiments of the present disclosure, service information detection time is shortened, and data circulation time is accelerated. Specifically, the reason why the detection time is long and the circulation time of the data is delayed is that: the service data are more, and the data are easy to miss in manual detection. Based on this, in the service information detection method of some embodiments of the present disclosure, first, a service information set of a supply end corresponding to a target service terminal in a preset period of time is obtained. Thus, the data is convenient to detect and analyze. And secondly, classifying the service information sets of the supply end to generate a first service information set and a second service information set. Therefore, the service information of the supply end of the missing data can be conveniently analyzed. And then, carrying out complement processing on each first supply end service information in the first supply end service information group so as to generate complement supply end service information and obtain a complement supply end service information group. Thus, the missing data can be complemented. And combining the second supply end service information set and the complement supply end service information set into a to-be-detected supply end service information set. Then, for each to-be-detected supply end service information in the to-be-detected supply end service information set, the following processing steps are executed: detecting the service information of the to-be-detected supply end to generate a detection result; and marking the service information of the to-be-detected supply end according to the detection result to generate service information of the detection supply end. Therefore, the detection and marking of the service information of the supply end can be completed, and the follow-up user can browse conveniently. And finally, carrying out encryption processing on each generated detection supply terminal service information to generate encryption supply terminal service information, obtaining an encryption supply terminal service information set, and storing the encryption supply terminal service information set into a target database. Thus, the confidentiality of service information is improved. The service information detection time is shortened, and the data circulation time is quickened.
Drawings
The above and other features, advantages, and aspects of embodiments of the present disclosure will become more apparent by reference to the following detailed description when taken in conjunction with the accompanying drawings. The same or similar reference numbers will be used throughout the drawings to refer to the same or like elements. It should be understood that the figures are schematic and that elements and components are not necessarily drawn to scale.
FIG. 1 is a flow chart of some embodiments of a traffic information detection method according to the present disclosure;
fig. 2 is a schematic structural diagram of some embodiments of a traffic information detection device according to the present disclosure;
fig. 3 is a schematic structural diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete. It should be understood that the drawings and embodiments of the present disclosure are for illustration purposes only and are not intended to limit the scope of the present disclosure.
It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings. Embodiments of the present disclosure and features of embodiments may be combined with each other without conflict.
It should be noted that the terms "first," "second," and the like in this disclosure are merely used to distinguish between different devices, modules, or units and are not used to define an order or interdependence of functions performed by the devices, modules, or units.
It should be noted that references to "one", "a plurality" and "a plurality" in this disclosure are intended to be illustrative rather than limiting, and those of ordinary skill in the art will appreciate that "one or more" is intended to be understood as "one or more" unless the context clearly indicates otherwise.
The names of messages or information interacted between the various devices in the embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.
The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 is a flow chart of some embodiments of a traffic information detection method according to the present disclosure. A flow 100 of some embodiments of a traffic information detection method according to the present disclosure is shown. The service information detection method comprises the following steps:
Step 101, obtaining a service information set of a supply end corresponding to a target service terminal in a preset time period.
In some embodiments, an execution body (e.g., a server) of the service information detection method may acquire, by using a wired connection or a wireless connection, a service information set of a supply end corresponding to the target service terminal in a preset period of time. Wherein, the supply end service information in the supply end service information set corresponds to a supply end, and the supply end service information in the supply end service information set includes: auditing duration, service order quantity, delivery time rate and quality sampling qualification rate. Here, the preset time period may be a preset time period. The target service terminal may refer to a user terminal. The supply end may be a terminal end that supplies various items. The audit duration may be an audit passing duration of an average one business order. The number of business orders may be the number of business orders. The shipping time rate may be a proportion of deferred shipping. The quality spot check yield may be a quality yield of each item of the spot check. The service information of the supply end may refer to information of each service order placed by the target service terminal in a supply end within a preset period of time.
Step 102, performing classification processing on the service information set of the supply end to generate a first service information set of the supply end and a second service information set of the supply end.
In some embodiments, the executing body may perform classification processing on the set of service information of the provider to generate a first service information set and a second service information set.
In practice, the executing body may execute the following classification step for each of the service information set of the service end:
first, determining whether a blank field exists in each field included in the service information of the supply end. Here, each field includes: auditing duration, service order quantity, delivery time rate and quality sampling qualification rate.
And a second step of generating at least one missing tag in response to determining that blank fields exist in the fields included in the service information of the supply end.
In practice, the second step may comprise the following sub-steps:
and a first sub-step of determining whether the auditing duration included in the service information of the supply end is empty.
And a second sub-step of generating an audit duration missing label in response to the fact that the audit duration is empty. That is, a text label indicating that the auditing duration is missing may be generated.
And a third sub-step of determining whether the number of service orders included in the service information of the supply end is empty.
And a fourth sub-step of generating a service order quantity missing tag in response to determining that the service order quantity is empty. That is, a text label indicating that the order quantity is missing may be generated.
And a fifth sub-step of determining whether the delivery time rate included in the service information of the supply end is empty.
And a sixth sub-step of generating a shipping time rate missing label in response to determining that the shipping time rate is empty. That is, a text label indicating that the shipping time rate is missing may be generated.
And seventh, determining whether the quality sampling qualification rate included in the service information of the supply end is empty.
And an eighth substep, in response to determining that the quality sampling inspection qualification rate is empty, generating a quality sampling inspection qualification rate missing label. That is, a text label indicating that the quality spot inspection yield is missing can be generated.
And thirdly, marking the service information of the supply end according to the at least one missing tag to generate marked service information of the supply end as first service information of the supply end. In practice, for each missing tag, the corresponding field in the above-mentioned service information of the supply end may be marked with the missing tag, so as to generate the marked service information of the supply end as the service information of the first supply end.
And fourth, in response to determining that the blank fields do not exist in the fields included in the service information of the supply end, determining the service information of the supply end as second service information of the supply end.
And 103, carrying out complement processing on each first supply end service information in the first supply end service information group so as to generate complement supply end service information and obtain a complement supply end service information group.
In some embodiments, the executing body may perform a completion process on each first supply side service information in the first supply side service information set to generate a completion supply side service information set, so as to obtain the completion supply side service information set. Namely, the data is completed according to the label marked in the first supply end service information. For example, the database may be queried for complete provider service information corresponding to the first provider service information. Then, the missing data in the first supply end service information can be complemented.
Step 104, combining the second service information set of the supply end with the complementary service information set of the supply end to be detected.
In some embodiments, the executing entity may combine the second set of provider service information with the complementary set of provider service information to form a set of provider service information to be detected.
Step 105, for each to-be-detected supply end service information in the to-be-detected supply end service information set, executing the following processing steps:
step 1051, performing detection processing on the to-be-detected service information of the supply end to generate a detection result.
In some embodiments, the executing body may perform detection processing on the to-be-detected service information of the supply end to generate a detection result.
In practice, the execution body may perform detection processing on the to-be-detected service information of the supply end through the following steps to generate a detection result:
determining whether the auditing time length included in the service information of the to-be-detected supply end is less than or equal to a preset time length.
And secondly, generating an abnormal auditing duration detection result in response to determining that the auditing duration is less than or equal to the preset duration. That is, a detection result indicating that the auditing time period is abnormal may be generated.
And thirdly, determining whether the number of the service orders included in the service information of the to-be-detected supply end is larger than or equal to the preset number.
And step four, generating an abnormal service order quantity detection result in response to determining that the service order quantity is greater than or equal to the preset quantity. That is, a detection result indicating that the number of service orders is abnormal may be generated.
And fifthly, determining whether the delivery time rate included in the service information of the to-be-detected supply end is smaller than or equal to the preset delivery time rate.
And a sixth step of generating an abnormal shipment time rate detection result in response to determining that the shipment time rate is equal to or less than a preset shipment time rate. That is, a detection result indicating that the shipment time rate is abnormal can be generated.
Seventh, determining whether the quality sampling inspection qualification rate included in the service information of the to-be-detected supply end is smaller than or equal to a preset quality sampling inspection qualification rate.
And eighth, generating an abnormal quality sampling inspection qualification rate detection result in response to determining that the quality sampling inspection qualification rate is less than or equal to a preset quality sampling inspection qualification rate. That is, a detection result indicating that the quality sampling inspection yield is abnormal can be generated.
In some optional implementations of some embodiments, the executing body may perform detection processing on the to-be-detected service information of the supply end to generate a detection result by: and inputting the service information of the supply end to be detected into a pre-trained service information detection model of the supply end to obtain a detection result. Here, the supply-side service information detection model may refer to a neural network model that is trained in advance, takes the to-be-detected supply-side service information as input, and takes the detection result as output. For example, the supply side traffic information detection model may refer to a convolutional neural network model.
Optionally, the service information detection model of the supply end is obtained through training the following steps:
first, determining an initial supply end service information detection model. The initial provisioning end service information detection model includes: the system comprises an initial auditing duration detection network, an initial service order quantity detection network, an initial shipping time rate detection network and an initial quality spot check qualification rate detection network. The initial supply side traffic information detection model may refer to an untrained convolutional neural network model. The initial audit duration detection network may refer to an untrained convolutional neural network. The initial traffic order quantity detection network may refer to an untrained convolutional neural network. The initial shipment time-rate detection network may refer to an untrained convolutional neural network. The initial quality spot check qualification network may refer to an untrained convolutional neural network.
And secondly, acquiring an audit duration sample group corresponding to the initial audit duration detection network. Here, the audit duration sample may refer to a sample of audit duration included in the service information of the supply end.
And thirdly, acquiring a service order quantity sample group corresponding to the initial service order quantity detection network. The service order quantity sample may refer to a sample of the service order quantity included in the service information at the donor.
And step four, acquiring a delivery time rate sample group corresponding to the initial delivery time rate detection network. The delivery time rate sample may refer to a sample of delivery time rates included in the service information at the supply end.
And fifthly, acquiring a quality sampling rate sample set corresponding to the initial quality sampling rate detection network. The quality sampling rate sample may refer to a sample of quality sampling rate included in the service information at the supply end.
And step six, training the initial supply end service information detection model according to the auditing duration sample group, the service order quantity sample group, the delivery time rate sample group and the quality sampling inspection qualification rate sample group to obtain a trained supply end service information detection model.
In practice, the sixth step may comprise the following sub-steps:
the first substep, deploying the initial auditing duration detection network on a first preset server, and synchronizing the auditing duration sample group to the first preset server. Here, the first preset server may be a server communicatively connected to the above-described execution subject.
And a second sub-step of controlling the first preset server to train the initial auditing duration detection network to obtain a trained auditing duration detection network. That is, the initial audit duration detection network may be trained in a training manner of the deep neural network.
And a third sub-step of deploying the initial service order quantity detection network on a second preset server and synchronizing the service order quantity sample group to the second preset server.
And a fourth sub-step of controlling the second preset server to train the initial service order quantity detection network to obtain a trained service order quantity detection network. The initial service order quantity detection network can be trained according to a training mode of the deep neural network.
And a fifth sub-step of deploying the initial shipment and time rate detection network on a third preset server and synchronizing the shipment and time rate sample group to the third preset server.
And a sixth substep, controlling the third preset server to train the initial delivery time rate detection network, and obtaining the trained delivery time rate detection network. The initial shipment time rate detection network can be trained according to a training mode of the deep neural network.
A seventh sub-step of deploying the initial quality sampling qualification rate detection network on a fourth preset server, and synchronizing the quality sampling qualification rate sample group to the fourth preset server.
And an eighth substep, controlling the fourth preset server to train the initial quality sampling inspection qualification rate detection network to obtain a trained quality sampling inspection qualification rate detection network. The initial quality sampling inspection qualification rate detection network can be trained according to a training mode of the deep neural network.
And a ninth substep, combining the trained auditing duration detection network, the service order quantity detection network, the shipping time rate detection network and the quality sampling inspection qualification rate detection network into a service information detection model of the supply end.
The related matters in the first sub-step-the ninth sub-step are taken as an invention point of the present disclosure, and the technical problem three' mentioned in the background art is solved, which is easy to cause abnormal data to flow out. ". Factors that easily cause abnormal data outflow are often as follows: the manual detection efficiency is lower, and the detection angle is single. If the above factors are solved, the effect of reducing the abnormal data outflow can be achieved. To achieve this, first, the initial audit duration detection network is deployed on a first preset server, and the audit duration sample set is synchronized to the first preset server. Secondly, the first preset server is controlled to train the initial auditing duration detection network, and the auditing duration detection network after training is obtained. Thus, the initial audit duration detection network can be trained at the first preset server. And secondly, deploying the initial service order quantity detection network on a second preset server, and synchronizing the service order quantity sample group to the second preset server. And then controlling the second preset server to train the initial service order quantity detection network to obtain a trained service order quantity detection network. Thus, the initial service order quantity detection network can be trained at the second preset server. And then, deploying the initial delivery time rate detection network on a third preset server, and synchronizing the delivery time rate sample group to the third preset server. And then, controlling the third preset server to train the initial delivery timing rate detection network to obtain a trained delivery timing rate detection network. Thus, the initial shipment time rate detection network can be trained at the third provisioning server. And then, deploying the initial quality sampling qualification rate detection network on a fourth preset server, and synchronizing the quality sampling qualification rate sample group to the fourth preset server. And then, controlling the fourth preset server to train the initial quality sampling inspection qualification rate detection network to obtain a trained quality sampling inspection qualification rate detection network. Thus, the fourth preset server can train the initial quality sampling inspection qualification rate detection network. And finally, combining the trained auditing duration detection network, the service order quantity detection network, the delivery time rate detection network and the quality sampling inspection qualification rate detection network into a service information detection model of the supply end. Therefore, the service information detection model of the supply end can be trained through a plurality of servers, and the training speed of the model is improved. In addition, the service information of the supply end can be detected from multiple angles. Thus, abnormal data outflow is reduced.
Step 1052, marking the service information of the to-be-detected supply end according to the detection result to generate service information of the detected supply end.
In some embodiments, the executing body may perform marking processing on the to-be-detected service information of the supply end according to the detection result, so as to generate detected service information of the supply end.
And 106, carrying out encryption processing on each generated detection supply terminal service information to generate encryption supply terminal service information, obtaining an encryption supply terminal service information set, and storing the encryption supply terminal service information set into a target database.
In some embodiments, the executing body may encrypt each of the generated detection provider service information to generate an encrypted provider service information set, obtain an encrypted provider service information set, and store the encrypted provider service information set in the target database. The detection of the service information of the supply end comprises the following steps: and (5) providing a terminal identifier. The supply identifier may uniquely represent a supply. The target database may refer to a database of target service terminals.
In practice, the executing body may encrypt each generated detection provider service information to generate encrypted provider service information by:
First, the supply end identification is coded to generate a supply end identification code. Here, the supply end identifier may be an english identifier. ASCII code value conversion can be carried out on the supply end identifier to obtain a supply end identifier code. That is, the english flag may be converted into a numerical value.
And secondly, carrying out the system processing on the supply end identification code to generate a system supply end identification value. Decimal conversion processing may be performed on the supply end identification code to generate a binary supply end identification value.
And thirdly, determining the sum of all preset prime numbers in the preset prime number array as a first encryption value. Here, the setting of the preset quality array is not limited.
And step four, determining the difference value between each preset prime number in the preset quality array and the identification value of the system supply end as an identification difference value, and obtaining an identification difference value group.
And fifthly, determining the sum of the identification differences in the identification difference group as a second encryption value.
Sixth, for each field value included in the detected service information of the supply end, the following processing steps are executed:
a first sub-step of encrypting the field value according to the first encrypted value and the second encrypted value to generate an encrypted field value. That is, the above-described field values may be symmetrically encrypted by the first encrypted value to generate the first encrypted field value. The field values may be symmetrically encrypted by a second encryption value to generate encrypted field values.
And a second sub-step of replacing the field value with the encrypted field value.
The related matters in the first step to the sixth step are taken as an invention point of the present disclosure, and the second technical problem mentioned in the background art is solved, which is easy to cause data leakage. ". Factors that easily cause data leakage are often as follows: because of certain sensitivity of the service data, the service data of each party is detected one by service personnel. If the above factors are solved, the effect of improving the confidentiality of the data can be achieved. To achieve this, first, the above-described supply-end identifier is subjected to encoding processing to generate a supply-end identifier code. Secondly, carrying out the system processing on the supply end identification code to generate a system supply end identification value. Therefore, the data can be encrypted by using the supply end identifier, so that the confidentiality of the data is improved. Then, the sum of all preset prime numbers in the preset prime number array is determined as a first encryption value. Then, determining the difference value between each preset prime number in the preset prime number array and the identification value of the system supply end as an identification difference value to obtain an identification difference value group; and determining the sum of the identification differences in the identification difference group as a second encryption value. Therefore, the preset quality array can be utilized to further improve the confidentiality of data. Then, for each field value included in the detected service information of the supply end, the following processing steps are executed: encrypting the field value according to the first encrypted value and the second encrypted value to generate an encrypted field value; and replacing the field value with the encrypted field value. Thereby, the data in the service information of the supply side can be replaced with encrypted data. Therefore, the confidentiality of service information of the supply end is improved.
With further reference to fig. 2, as an implementation of the method shown in the above figures, the present disclosure provides embodiments of a service information detection apparatus, which correspond to those method embodiments shown in fig. 1, and which are particularly applicable to various electronic devices.
As shown in fig. 2, the service information detection apparatus 200 of some embodiments includes: an acquisition unit 201, a classification unit 202, a complementing unit 203, a combining unit 204, a detection unit 205, and an encryption unit 206. The obtaining unit 201 is configured to obtain a set of supply end service information corresponding to the target service terminal in a preset period, where the supply end service information in the set of supply end service information corresponds to a supply end, and the supply end service information in the set of supply end service information includes: auditing duration, service order quantity, delivery time rate and quality sampling qualification rate; a classification unit 202 configured to perform classification processing on the service information set of the supply end, so as to generate a first service information set of the supply end and a second service information set of the supply end; a complementing unit 203 configured to perform complementing processing on each first supply-side service information in the first supply-side service information group, so as to generate complementing supply-side service information, and obtain a complementing supply-side service information group; a combining unit 204 configured to combine the second service information set and the complementary service information set into a service information set of a to-be-detected service; the detecting unit 205 is configured to perform, for each to-be-detected supply side service information in the to-be-detected supply side service information set, the following processing steps: detecting the service information of the to-be-detected supply end to generate a detection result; marking the service information of the to-be-detected supply end according to the detection result to generate service information of the detection supply end; the encryption unit 206 is configured to encrypt each of the generated detection provider service information to generate encrypted provider service information, obtain an encrypted provider service information set, and store the encrypted provider service information set in the target database.
It will be appreciated that the elements described in the traffic information detection device 200 correspond to the respective steps in the method described with reference to fig. 1. Thus, the operations, features and advantages described above for the method are equally applicable to the service information detection apparatus 200 and the units contained therein, and are not described herein again.
Referring now to fig. 3, a schematic diagram of an electronic device (e.g., server) 300 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic devices in some embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), car terminals (e.g., car navigation terminals), and the like, as well as stationary terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 3 is merely an example and should not impose any limitations on the functionality and scope of use of embodiments of the present disclosure.
As shown in fig. 3, the electronic device 300 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 301 that may perform various suitable actions and processes in accordance with a program stored in a Read Only Memory (ROM) 302 or a program loaded from a storage means 308 into a Random Access Memory (RAM) 303. In the RAM303, various programs and data required for the operation of the electronic apparatus 300 are also stored. The processing device 301, the ROM302, and the RAM303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
In general, the following devices may be connected to the I/O interface 305: input devices 306 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 307 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 308 including, for example, magnetic tape, hard disk, etc.; and communication means 309. The communication means 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. While fig. 3 shows an electronic device 300 having various means, it is to be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead. Each block shown in fig. 3 may represent one device or a plurality of devices as needed.
In particular, according to some embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flow chart. In such embodiments, the computer program may be downloaded and installed from a network via communications device 309, or from storage device 308, or from ROM 302. The above-described functions defined in the methods of some embodiments of the present disclosure are performed when the computer program is executed by the processing means 301.
It should be noted that, the computer readable medium described in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, the computer-readable signal medium may comprise a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.
In some implementations, the clients, servers may communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol ), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the internet (e.g., the internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed networks.
The computer readable medium may be contained in the electronic device; or may exist alone without being incorporated into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring a supply end service information set corresponding to a target service terminal in a preset time period, wherein the supply end service information in the supply end service information set corresponds to a supply end, and the supply end service information in the supply end service information set comprises: auditing duration, service order quantity, delivery time rate and quality sampling qualification rate; classifying the service information sets of the supply end to generate a first service information set of the supply end and a second service information set of the supply end; performing completion processing on each first supply end service information in the first supply end service information group to generate completion supply end service information, and obtaining a completion supply end service information group; combining the second supply end service information group and the complement supply end service information group into a supply end service information set to be detected; for each to-be-detected supply end service information in the to-be-detected supply end service information set, executing the following processing steps: detecting the service information of the to-be-detected supply end to generate a detection result; marking the service information of the to-be-detected supply end according to the detection result to generate service information of the detection supply end; and carrying out encryption processing on each generated detection supply terminal service information to generate encryption supply terminal service information, obtaining an encryption supply terminal service information set, and storing the encryption supply terminal service information set into a target database.
Computer program code for carrying out operations for some embodiments of the present disclosure may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in some embodiments of the present disclosure may be implemented by means of software, or may be implemented by means of hardware. The described units may also be provided in a processor, for example, described as: a processor comprising: the device comprises an acquisition unit, a classification unit, a complement unit, a combination unit, a detection unit and an encryption unit. The names of these units do not in some cases limit the unit itself, for example, the classification unit may also be described as "a unit that performs classification processing on the above-mentioned set of service information of the provider to generate the first service information group and the second service information group".
The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.
The foregoing description is only of the preferred embodiments of the present disclosure and description of the principles of the technology being employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above technical features, but encompasses other technical features formed by any combination of the above technical features or their equivalents without departing from the spirit of the invention. Such as the above-described features, are mutually substituted with (but not limited to) the features having similar functions disclosed in the embodiments of the present disclosure.
Claims (7)
1. A service information detection method includes:
acquiring a supply end service information set corresponding to a target service terminal in a preset time period, wherein supply end service information in the supply end service information set corresponds to a supply end, and the supply end service information in the supply end service information set comprises: auditing duration, service order quantity, delivery time rate and quality sampling qualification rate;
classifying the service information set of the supply end to generate a first service information set of the supply end and a second service information set of the supply end;
performing completion processing on each first supply end service information in the first supply end service information group to generate completion supply end service information, and obtaining a completion supply end service information group;
combining the second supply end service information group with the complement supply end service information to be a supply end service information set to be detected, wherein the detection of the supply end service information comprises the following steps: a supply end identifier;
for each to-be-detected supply end service information in the to-be-detected supply end service information set, executing the following processing steps:
detecting the service information of the to-be-detected supply end to generate a detection result;
Marking the service information of the to-be-detected supply end according to the detection result to generate service information of the detection supply end;
encrypting each generated detection supply terminal service information to generate an encryption supply terminal service information set, and storing the encryption supply terminal service information set into a target database;
the encrypting processing is performed on each generated detection supply end service information to generate encrypted supply end service information, which includes:
coding the supply end identifier to generate a supply end identifier code;
carrying out a binary process on the supply end identification code to generate a binary supply end identification value;
determining the sum of all preset prime numbers in the preset prime number array as a first encryption value;
determining the difference value between each preset prime number in the preset prime number array and the identification value of the system supply end as an identification difference value to obtain an identification difference value group;
determining the sum of all the identification differences in the identification difference group as a second encryption value;
for each field value included in the detection provider service information, executing the following processing steps:
Encrypting the field value according to the first encrypted value and the second encrypted value to generate an encrypted field value;
replacing the field value with the encrypted field value;
the detecting the service information of the to-be-detected supply end to generate a detection result includes:
inputting the service information of the supply end to be detected into a pre-trained service information detection model of the supply end to obtain a detection result;
the service information detection model of the supply end is obtained through training the following steps:
determining an initial supply end service information detection model, wherein the initial supply end service information detection model comprises: an initial auditing duration detection network, an initial service order quantity detection network, an initial shipping time rate detection network and an initial quality spot check qualification rate detection network;
acquiring an audit duration sample group corresponding to the initial audit duration detection network;
acquiring a service order quantity sample group corresponding to the initial service order quantity detection network;
acquiring a delivery time rate sample group corresponding to the initial delivery time rate detection network;
acquiring a quality sampling inspection qualification rate sample set corresponding to the initial quality sampling inspection qualification rate detection network; training the initial supply end service information detection model according to the auditing duration sample group, the service order quantity sample group, the delivery time rate sample group and the quality sampling inspection qualification rate sample group to obtain a trained supply end service information detection model;
The training of the initial supply end service information detection model according to the audit duration sample group, the service order quantity sample group, the delivery time rate sample group and the quality sampling inspection qualification rate sample group to obtain a trained supply end service information detection model comprises the following steps:
deploying the initial auditing duration detection network on a first preset server, and synchronizing the auditing duration sample group to the first preset server;
controlling the first preset server to train the initial auditing duration detection network to obtain a trained auditing duration detection network;
deploying the initial service order quantity detection network on a second preset server, and synchronizing the service order quantity sample group to the second preset server;
controlling the second preset server to train the initial service order quantity detection network to obtain a trained service order quantity detection network;
deploying the initial shipment and time rate detection network on a third preset server, and synchronizing the shipment and time rate sample group to the third preset server;
controlling the third preset server to train the initial delivery timing rate detection network to obtain a trained delivery timing rate detection network;
Deploying the initial quality sampling inspection qualification rate detection network on a fourth preset server, and synchronizing the quality sampling inspection qualification rate sample set to the fourth preset server;
controlling the fourth preset server to train the initial quality sampling inspection qualification rate detection network to obtain a trained quality sampling inspection qualification rate detection network;
and combining the trained auditing duration detection network, the service order quantity detection network, the delivery time rate detection network and the quality sampling inspection qualification rate detection network into a service information detection model of the supply end.
2. The method of claim 1, wherein the classifying the set of provisioning side traffic information to generate a first set of provisioning side traffic information and a second set of provisioning side traffic information comprises:
for each of the set of provisioning side service information, performing the classification step of:
determining whether blank fields exist in each field included in the service information of the supply end;
generating at least one missing tag in response to determining that blank fields exist in each field included in the service information of the supply end;
marking the service information of the supply end according to the at least one missing tag to generate marked service information of the supply end as first service information of the supply end;
And determining the supply end service information as second supply end service information in response to determining that blank fields do not exist in the fields included in the supply end service information.
3. The method of claim 2, wherein the generating at least one missing tag in response to determining that there is a blank field in each field included in the provisioning side service information comprises:
determining whether the auditing duration included in the service information of the supply end is empty or not;
generating an audit duration missing tag in response to determining that the audit duration is empty;
determining whether the service order number included in the service information of the supply end is empty;
generating a service order quantity missing tag in response to determining that the service order quantity is empty;
determining whether the delivery time rate included in the service information of the supply end is empty;
generating a shipping time rate miss tag in response to determining that the shipping time rate is empty;
determining whether the quality sampling inspection qualification rate included in the service information of the supply end is empty;
and generating a quality sampling inspection qualification rate missing label in response to determining that the quality sampling inspection qualification rate is empty.
4. The method of claim 1, wherein the detecting the to-be-detected supply side service information to generate a detection result includes:
Determining whether the auditing time length included in the service information of the to-be-detected supply end is less than or equal to a preset time length;
generating an abnormal auditing duration detection result in response to determining that the auditing duration is less than or equal to a preset duration;
determining whether the number of service orders included in the service information of the to-be-detected supply end is greater than or equal to a preset number;
generating an abnormal service order quantity detection result in response to determining that the service order quantity is greater than or equal to a preset quantity;
determining whether the delivery time rate included in the service information of the supply end to be detected is smaller than or equal to a preset delivery time rate;
generating an abnormal shipping time rate detection result in response to determining that the shipping time rate is less than or equal to a preset shipping time rate;
determining whether the quality sampling inspection qualification rate included in the service information of the to-be-detected supply end is smaller than or equal to a preset quality sampling inspection qualification rate;
and generating an abnormal quality sampling inspection qualification rate detection result in response to determining that the quality sampling inspection qualification rate is smaller than or equal to a preset quality sampling inspection qualification rate.
5. A traffic information detection apparatus comprising:
the system comprises an acquisition unit configured to acquire a supply end service information set corresponding to a target service terminal in a preset time period, wherein the supply end service information in the supply end service information set corresponds to a supply end, and the supply end service information in the supply end service information set comprises: auditing duration, service order quantity, delivery time rate and quality sampling qualification rate;
The classification unit is configured to perform classification processing on the service information set of the supply end so as to generate a first service information set of the supply end and a second service information set of the supply end;
the completion unit is configured to perform completion processing on each first supply end service information in the first supply end service information group so as to generate completion supply end service information and obtain a completion supply end service information group;
a combining unit configured to combine the second supply end service information group and the complement supply end service information group into a supply end service information set to be detected, wherein detecting the supply end service information includes: a supply end identifier;
the detection unit is configured to execute the following processing steps for each to-be-detected supply end service information in the to-be-detected supply end service information set: detecting the service information of the to-be-detected supply end to generate a detection result; marking the service information of the to-be-detected supply end according to the detection result to generate service information of the detection supply end; a detection unit further configured to:
inputting the service information of the supply end to be detected into a pre-trained service information detection model of the supply end to obtain a detection result;
The service information detection model of the supply end is obtained through training the following steps:
determining an initial supply end service information detection model, wherein the initial supply end service information detection model comprises: an initial auditing duration detection network, an initial service order quantity detection network, an initial shipping time rate detection network and an initial quality spot check qualification rate detection network;
acquiring an audit duration sample group corresponding to the initial audit duration detection network;
acquiring a service order quantity sample group corresponding to the initial service order quantity detection network;
acquiring a delivery time rate sample group corresponding to the initial delivery time rate detection network;
acquiring a quality sampling inspection qualification rate sample set corresponding to the initial quality sampling inspection qualification rate detection network;
training the initial supply end service information detection model according to the auditing duration sample group, the service order quantity sample group, the delivery time rate sample group and the quality sampling inspection qualification rate sample group to obtain a trained supply end service information detection model;
the training of the initial supply end service information detection model according to the audit duration sample group, the service order quantity sample group, the delivery time rate sample group and the quality sampling inspection qualification rate sample group to obtain a trained supply end service information detection model comprises the following steps:
Deploying the initial auditing duration detection network on a first preset server, and synchronizing the auditing duration sample group to the first preset server;
controlling the first preset server to train the initial auditing duration detection network to obtain a trained auditing duration detection network;
deploying the initial service order quantity detection network on a second preset server, and synchronizing the service order quantity sample group to the second preset server;
controlling the second preset server to train the initial service order quantity detection network to obtain a trained service order quantity detection network;
deploying the initial shipment and time rate detection network on a third preset server, and synchronizing the shipment and time rate sample group to the third preset server;
controlling the third preset server to train the initial delivery timing rate detection network to obtain a trained delivery timing rate detection network;
deploying the initial quality sampling inspection qualification rate detection network on a fourth preset server, and synchronizing the quality sampling inspection qualification rate sample set to the fourth preset server;
Controlling the fourth preset server to train the initial quality sampling inspection qualification rate detection network to obtain a trained quality sampling inspection qualification rate detection network;
combining the trained auditing duration detection network, the service order quantity detection network, the delivery time rate detection network and the quality sampling inspection qualification rate detection network into a service information detection model of a supply end;
the encryption unit is configured to encrypt each generated detection supply terminal service information to generate encryption supply terminal service information, obtain an encryption supply terminal service information set and store the encryption supply terminal service information set into a target database; an encryption unit further configured to:
coding the supply end identifier to generate a supply end identifier code;
carrying out a binary process on the supply end identification code to generate a binary supply end identification value;
determining the sum of all preset prime numbers in the preset prime number array as a first encryption value;
determining the difference value between each preset prime number in the preset prime number array and the identification value of the system supply end as an identification difference value to obtain an identification difference value group;
determining the sum of all the identification differences in the identification difference group as a second encryption value;
For each field value included in the detection provider service information, executing the following processing steps:
encrypting the field value according to the first encrypted value and the second encrypted value to generate an encrypted field value;
and replacing the field value with the encrypted field value.
6. An electronic device, comprising:
one or more processors;
a storage device having one or more programs stored thereon;
when executed by the one or more processors, causes the one or more processors to implement the method of any of claims 1-4.
7. A computer readable medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements the method of any of claims 1-4.
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