CN114422227A - Data acquisition and analysis system based on network security - Google Patents
Data acquisition and analysis system based on network security Download PDFInfo
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- CN114422227A CN114422227A CN202210038815.3A CN202210038815A CN114422227A CN 114422227 A CN114422227 A CN 114422227A CN 202210038815 A CN202210038815 A CN 202210038815A CN 114422227 A CN114422227 A CN 114422227A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/12—Applying verification of the received information
- H04L63/123—Applying verification of the received information received data contents, e.g. message integrity
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- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
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- H—ELECTRICITY
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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Abstract
The invention relates to a data acquisition and analysis system based on network security, which comprises a data acquisition client, a plurality of data collection servers and a data analysis server, wherein the data acquisition client is connected with the data collection servers through a network; the data acquisition client acquires data regularly, stores the acquired data in K randomly selected data acquisition servers respectively, and sends a data acquisition indication packet for indicating a data storage form to the data analysis server; the data analysis server may obtain data for data analysis based on the data collection indication packet.
Description
[ technical field ] A method for producing a semiconductor device
The invention belongs to the field of computers and network security, and particularly relates to a data acquisition and analysis system based on network security.
[ background of the invention ]
In the existing enterprise production and operation process, large-scale data acquisition and analysis are often required. Taking an intelligent automobile as an example, an automobile manufacturer generally needs to collect driving data of each intelligent automobile for analysis, so as to find out possible problems in the aspects of automobile hardware and software, and facilitate subsequent further software update or hardware improvement.
The large-scale collected data is generally transmitted through a network, that is, each data collection client (for example, a smart car) transmits the collected data to a designated server (for example, a server owned by a car manufacturer) through a wireless or wired network (for example, a 5G communication network). The server stores all the collected data, extracts the stored data as needed, and performs further analysis.
However, when the data collected by the data collection client is transmitted over the network, the data security problem is involved. On one hand, the data collected by the system may include user personal data, and the user personal data needs to be prevented from being leaked when the data is transmitted on the network; on the other hand, in order to ensure the reliability of data analysis, the possibility of tampering when data is transmitted over a network should be avoided. In the prior art, an encryption transmission method is usually adopted to solve the problem of network security, that is, a data acquisition client encrypts data and sends the encrypted data to a designated server, and then the designated server decrypts the data. However, in large-scale data collection, this solution puts a great deal of pressure on the server, because the server needs to perform a lot of resource-consuming decryption work, and in addition, the designated server becomes a security weakness in the system, and once the designated server has a problem, the data may be leaked.
[ summary of the invention ]
In order to solve the above problems in the prior art, the present invention provides a data acquisition and analysis system based on network security.
The technical scheme adopted by the invention is as follows:
a data acquisition and analysis system based on network security comprises a data acquisition client, a plurality of data collection servers and a data analysis server; the data acquisition client is used for acquiring data specified by the system, the data collection server is used for receiving and storing the data uploaded by the data acquisition client, and the data analysis server is used for analyzing the acquired data; the system achieves data acquisition and analysis by performing the following steps:
(1) the data acquisition client acquires data according to a predefined rule, and generates a corresponding data packet at regular time, namely, the packet Package is { ID, time, data }, wherein the ID is a unique identifier of the data acquisition client, the time is a timestamp of the current time, and the data is acquired data;
(2) the data acquisition client randomly selects K data acquisition servers as target servers, wherein K is more than or equal to 3;
(3) the data acquisition client generates K random numbers D1，D2，……，DKAnd satisfies the following formula:
wherein D is a security code of the data acquisition client;
(4) the data acquisition client side constructs K data sub-packets, the ith data sub-packet Pi＝{ID，time，DiI is more than or equal to 1 and less than or equal to K; the data acquisition client side sends the ith data sub-packet PiSend to the selected ith data collection server CServeri；
(5) The data acquisition client side constructs a data collection indication packet Collector, namely Collector ═ ID, time and CSID1，CSID2，……，CSIDK}; wherein, the data collection server CServeriIs CSIDi(ii) a Then the data acquisition client sends the data collection indication packet Collector to the data analysis server;
(6) the data analysis server determines a corresponding binary group < ID, time > according to data to be analyzed, and determines a corresponding data collection indication packet according to the binary group;
(7) the data analysis server sends a data acquisition request to each data collection server indicated by the data collection indication packet according to the data collection indication packet so as to receive a corresponding data sub-packet from the data collection server;
(8) the data collection server inquires and acquires a data sub-packet corresponding to the data acquisition request according to the received data acquisition request, and returns the acquired data sub-packet to the data analysis server; after receiving the data sub-package, the data analysis server judges whether the identifier ID and the data time stamp time in the data sub-package are correct or not, discards the incorrect data sub-package, and stores the correct data sub-package
(9) And the data analysis server calculates the data acquired by the data acquisition client according to the acquired data sub-packets and the corresponding security codes of the data acquisition client, and executes a corresponding data analysis algorithm.
Further, the data acquisition client is installed in the intelligent automobile.
Further, the predefined rules include the type of data collected, the manner in which the data was collected.
Further, K is a predefined value in the data collection client.
Further, the value of K is dynamically determined according to the size of the data volume in the data packet or the safety requirement of the data.
Further, the security code D is a security value pre-stored in the data acquisition client; the security code is a large randomly generated integer, the system manufacturer generates the security code in advance and stores the security code in the corresponding data acquisition client, and meanwhile, the security code and the ID of the data acquisition client are stored in the data analysis server in an associated mode.
Further, the data analysis server carries a plurality of different duplets in one data acquisition request.
Further, the data collection server determines and returns a plurality of data sub-packets according to the plurality of different duplets.
Further, after receiving the data sub-packet replied by the data collection server, the data analysis server judges whether the ID and the time in the data sub-packet are the same as a certain binary group in the data acquisition request, if the two binary groups are the same, the data sub-packet is correct, otherwise, the data sub-packet is incorrect.
Further, the data analysis server determines to reserve or delete the acquired collected data according to a system security policy.
The invention has the beneficial effects that: in the data acquisition and analysis system, the safety of data transmission and storage on the network is improved, and the pressure on the server is reduced.
[ description of the drawings ]
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, and are not to be considered limiting of the invention, in which:
FIG. 1 is a schematic diagram of the data acquisition and analysis system of the present invention.
[ detailed description ] embodiments
The present invention will now be described in detail with reference to the drawings and specific embodiments, wherein the exemplary embodiments and descriptions are provided only for the purpose of illustrating the present invention and are not to be construed as limiting the present invention.
As shown in fig. 1, the data collection and analysis system of the present invention includes one or more data collection clients, a plurality of data collection servers, and a data analysis server.
The data acquisition client is used for acquiring data specified by the system, and is usually installed in a certain terminal device. Still taking the intelligent vehicle as an example, a software module of the data acquisition client may be installed in the operating system of the intelligent vehicle, or a hardware module of the data acquisition client may also be directly installed in the intelligent vehicle, which is not limited in this invention. After the data acquisition client is operated, the data acquisition client can acquire pre-specified data in the intelligent automobile, such as a driving route of the intelligent automobile, related operation data of an automatic driving system of the automobile, related videos and operation data of automobile accidents and the like. After the permission of the user, the data collected by the data collecting client can be uploaded to the data collecting server of the invention through the communication module in the intelligent automobile. For smart cars, the communication module is typically connected to the internet via a mobile communication network, such as the common 4G or 5G mobile communication network. Of course, for the data collection client in other embodiments, it may also connect to the internet through a wired network and upload data, which is not limited in the present invention.
In short, the data acquisition client can be respectively installed in a large number of different terminal devices, the data acquisition analysis system of the invention can also have a large number of data acquisition clients, and each data acquisition client acquires predefined data in the terminal device in real time and uploads the predefined data through the network at regular time, so the invention can acquire and analyze massive terminal device data.
The data collection server is used for receiving and storing data uploaded by the data collection client, and a plurality of data collection servers are used for receiving and storing the uploaded data in consideration of the pressure of massive uploaded data on the server and the safety of data storage, so that the pressure of the server is relieved through data splitting and distributed storage, and the safety of the data is ensured.
The data analysis server is used for analyzing the acquired data, is independent of the data collection server, and respectively acquires the required data from the data collection servers and performs corresponding processing and analysis. The data analysis server may execute different data analysis algorithms to implement different data analysis functions according to the needs, which is not limited in the present invention.
Based on the data acquisition and analysis system, the specific data acquisition and analysis process of the present invention is described in detail below.
(1) The data acquisition client acquires data according to a predefined rule and generates a corresponding data packet at regular time.
Specifically, the predefined rule includes a type of data to be collected, a manner of collecting data, and the like. In the case of an intelligent car, the type of the collected data may include, for example, a driving route of the car, a speed of the car, and the like. The manner in which the data is acquired may include, for example, real-time acquisition, timed acquisition, and the like. The data acquisition client stores acquired data in a designated memory first, and generates corresponding data packets according to the content in the memory at regular intervals, namely, the data acquired in the past time period is packaged to generate the data packets needing to be uploaded. For example, the data collection client generates a corresponding data packet every other day, and the data packet includes data collected by the data collection client in the past day.
The data packet needs to include a unique identifier ID of the data acquisition client and a timestamp time of the current time in addition to the acquired data. Namely, the packet Package is { ID, time, data }, and since the data acquisition client generates one packet at regular intervals, the binary < ID, time > can actually uniquely identify one packet in the subsequent flow.
(2) And the data acquisition client randomly selects K data acquisition servers as target servers.
As described above, the data collection and analysis system of the present invention includes a plurality of data collection servers, and assuming that there are N data collection servers, the data collection client randomly selects K data collection servers (K ≦ N) from the N data collection servers. To ensure data security, the system requires that the value of K should not be less than a predefined security threshold, e.g., K ≧ 3.
According to a specific embodiment of the present invention, K may be a predefined value in the data collection client, and the value of K may be different for each data collection client. According to another embodiment of the present invention, K may be dynamically determined according to the size of the data amount in the data packet or the security requirement of the data, for example, the larger the data packet is, the larger the value of K is; the higher the security requirement on the data is, the larger the K value is; in this case, the K value determined by the same data acquisition client every time the data acquisition client uploads may be different.
(3) The data acquisition client generates K random numbers D1，D2，……，DKAnd satisfies the following formula:
wherein D is a security code of the data acquisition client, and the security code D is a security value pre-stored in the data acquisition client. The security code is a large randomly generated integer, the system manufacturer generates the security code in advance and stores the security code in the corresponding data acquisition client, and meanwhile, the security code and the ID of the data acquisition client are stored in the data analysis server in an associated mode.
For example, a manufacturer of a smart car may previously embed a security code of the smart car in a security memory of the smart car when the smart car is produced. Preferably, the secure memory may prevent reading by devices other than the data collection client to ensure security of the security code. Meanwhile, the association information < D, ID > is stored in the data analysis server.
(4) And the data acquisition client sends the K random numbers to the K data collection servers respectively, and each data collection server receives one of the random numbers.
Suppose that, in step 2, the K data collection servers selected by the data collection client are CServer servers respectively1，CServer2，……，CServerKThe data acquisition client needs to send a random number D1Sent to CServer1Random number D2Sent to CServer2And so on.
In specific operation, the data acquisition client needs to construct K data sub-packets, and each digital sub-packet includes the unique identifier ID of the data acquisition client, the timestamp time and a corresponding random number, i.e., the ith data sub-packet Pi＝{ID，time，DiAnd (1 < i < K). Then the data acquisition client side enables the ith data sub-package PiSend to the selected ith data collection server CServeri. Each data collection server stores the data sub-packets it receives for subsequent use.
(5) And the data acquisition client sends the identifiers of the selected K data collection servers to the data analysis server.
Assume that the data collection server CServeriIs CSIDiThe data collection client sends the unique identifier ID of the data collection client, the timestamp time and the identifiers CSID of the K data collection serversiAnd (i is more than or equal to 1 and less than or equal to K) sending the data to the data analysis server.
In a specific operation, the data collection client needs to construct a data collection indication packet Collector, i.e. Collector ═ ID, time, CSID1，CSID2，……，CSIDK}. And then the data acquisition client sends the data collection indication packet Collector to the data analysis server, and the data analysis server stores the received data collection indication packet for subsequent use.
And the data acquisition client finishes the uploading work of the acquired data, and the data acquisition client acquires and uploads the data at intervals of a certain time period, so that the data acquisition client needs to execute the steps 1-5 once every time the data is acquired and uploaded. It should be noted that, each time the data is collected and uploaded, the data collection client randomly selects K data collection servers when executing step 2. That is, even for the same data collection client, the K data collection servers selected each time the data collection client collects and uploads data may be different and are all selected randomly; this way the security of the system data is enhanced.
It can also be seen from the above steps that the collected data is actually stored in the randomly selected K data collection servers in a distributed storage manner, which reduces the operating pressure of each server. Although the data analysis server does not receive the uploaded data, the data is specifically distributed in a manner of being stored in the data analysis server. Therefore, in order to acquire the acquired data, the data analysis server needs to summarize data of the K data collection servers, and the data cannot be acquired by simply controlling one or a small number of servers, so that the security of network data is greatly improved.
After the data is collected and uploaded, the data analysis server can perform data analysis according to the uploaded data when needed, and in order to perform data analysis, the data analysis server first needs to restore the data according to the data collection instruction packet.
(6) The data analysis server determines the corresponding binary group < ID, time > according to the data to be analyzed, and determines the corresponding data collection indication packet according to the binary group.
Specifically, the data analysis server may execute a corresponding data analysis algorithm on a designated data set according to the setting of the administrator, and the actual data of the data set is distributed on different data collection servers. Therefore, the data analysis server needs to determine the data it needs to analyze, i.e. which data collection clients collected the uploaded data in which time period, in other words, the data analysis server needs to determine the identifier ID of one or more data collection clients, and for each ID, determine the timestamp time of the uploaded data that falls in the above time period. In this way, the data analysis server determines a series of duplets corresponding to the data set, each including the ID of the data collection client and the corresponding data timestamp time. Further, based on each duplet, its corresponding data collection indication packet, i.e. Collector ═ ID, time, CSID, may be determined1，CSID2，……，CSIDK}。
(7) And the data analysis server sends a data acquisition request to each data collection server indicated by the data collection indication packet according to the data collection indication packet so as to receive a corresponding data sub-packet from the data collection server.
Specifically, the data analysis server sends the CSID to the data analysis serveri(i is more than or equal to 1 and less than or equal to K) corresponding data collection server CServeriSending a data acquisition request including the binary group<ID，time>. The data collection server can determine the data sub-package P stored by the data collection server according to the binary groupi＝{ID，time，DiAnd then returning the data sub-packets to the data analysis server.
In order to reduce the number of interactions, the data analysis server may also carry a plurality of different duplets in one data acquisition request, so that the data collection server may determine and return a plurality of data sub-packets at a time.
(8) The data collection server inquires and acquires a data sub-packet corresponding to the data acquisition request according to the received data acquisition request, and returns the acquired data sub-packet to the data analysis server; and after receiving the data sub-packets, the data analysis server judges whether the identifier ID and the data timestamp time in the data sub-packets are correct, discards incorrect data sub-packets and stores correct data sub-packets.
Specifically, after receiving a data acquisition request, the data collection server parses one or more binary groups from the data acquisition request, and analyzes the two binary groups according to the parsed binary groups<ID，time>The data collection server can inquire and obtain the corresponding data sub-package Pi＝{ID，time，Di}. In this way, the data collection server may obtain one or more data sub-packets corresponding to the data acquisition request and return them to the data analysis server.
After receiving the data sub-packet replied by the data collection server, the data analysis server can firstly judge whether the ID and the time in the data sub-packet are the same as a certain binary group in the data acquisition request, if the ID and the time in the data sub-packet are the same as the certain binary group in the data acquisition request, the data sub-packet is correct, otherwise, the data sub-packet is incorrect, and the data analysis server can directly discard the incorrect data sub-packet.
(9) And the data analysis server calculates the data acquired by the data acquisition client according to the acquired data sub-packets and the corresponding security codes of the data acquisition client.
In particular, as previously described, the data analysis server stores the security code of the data collection client, and thus for a tuple<ID，time>The data analysis server can obtain the security code D corresponding to the ID and obtain the corresponding K data sub-packets Pi＝{ID，time，Di}(1≤i≤K)。
The data analysis server can then calculate the data collected, i.e. data
Thus, the data analysis server obtains the data to be analyzed through the data collection server, and can execute various data analysis algorithms on the data. The specific data analysis process is not the focus of the present invention and will not be described herein.
According to an embodiment of the invention, after the data analysis process is completed, the data analysis server may store the collected data in its own database for later use. According to another embodiment of the present invention, for higher security, the data analysis server may also delete the acquired collected data, and then acquire the collected data from the data collection server again when necessary. Which way to use depends on the security policy of the system.
The above description is only a preferred embodiment of the present invention, and all equivalent changes or modifications of the structure, characteristics and principles described in the present invention are included in the scope of the present invention.
Claims (10)
1. A data acquisition and analysis system based on network security is characterized by comprising a data acquisition client, a plurality of data collection servers and a data analysis server; the data acquisition client is used for acquiring data specified by the system, the data collection server is used for receiving and storing the data uploaded by the data acquisition client, and the data analysis server is used for analyzing the acquired data; the system achieves data acquisition and analysis by performing the following steps:
(1) the data acquisition client acquires data according to a predefined rule, and generates a corresponding data packet at regular time, namely, the packet Package is { ID, time, data }, wherein the ID is a unique identifier of the data acquisition client, the time is a timestamp of the current time, and the data is acquired data;
(2) the data acquisition client randomly selects K data acquisition servers as target servers, wherein K is more than or equal to 3;
(3) the data acquisition client generates K random numbers D1，D2，……，DKAnd satisfies the following formula:
wherein D is a security code of the data acquisition client;
(4) the data acquisition client side constructs K data sub-packets, the ith data sub-packet Pi＝{ID，time，DiI is more than or equal to 1 and less than or equal to K; the data acquisition client side sends the ith data sub-packet PiSend to the selected ith data collection server CServeri；
(5) The data acquisition client side constructs a data collection indication packet Collector, namely Collector ═ ID, time and CSID1，CSID2，……，CSIDK}; wherein, the data collection server CServeriIs CSIDi(ii) a Then the data acquisition client sends the data collection indication packet Collector to the data analysis server;
(6) the data analysis server determines a corresponding binary group < ID, time > according to data to be analyzed, and determines a corresponding data collection indication packet according to the binary group;
(7) the data analysis server sends a data acquisition request to each data collection server indicated by the data collection indication packet according to the data collection indication packet so as to receive a corresponding data sub-packet from the data collection server;
(8) the data collection server inquires and acquires a data sub-packet corresponding to the data acquisition request according to the received data acquisition request, and returns the acquired data sub-packet to the data analysis server; after receiving the data sub-package, the data analysis server judges whether the identifier ID and the data time stamp time in the data sub-package are correct or not, discards the incorrect data sub-package, and stores the correct data sub-package
(9) And the data analysis server calculates the data acquired by the data acquisition client according to the acquired data sub-packets and the corresponding security codes of the data acquisition client, and executes a corresponding data analysis algorithm.
2. The data collection and analysis system of claim 1, wherein the data collection client is installed in a smart car.
3. The data collection analysis system of any of claims 1-2, wherein the predefined rules include a type of data collected, a manner in which the data was collected.
4. A data collection analysis system according to any one of claims 1 to 3, wherein K is a predefined value in the data collection client.
5. The data collection and analysis system of any one of claims 1-3, wherein the value of K is dynamically determined based on the size of the data volume in the data packet or the security requirements of the data.
6. The data collection and analysis system of claim 1, wherein the security code D is a security value pre-stored in the data collection client; the security code is a large randomly generated integer, the system manufacturer generates the security code in advance and stores the security code in the corresponding data acquisition client, and meanwhile, the security code and the ID of the data acquisition client are stored in the data analysis server in an associated mode.
7. The data collection and analysis system of claim 1, wherein the data analysis server carries a plurality of different duplets in a data acquisition request.
8. The data collection analysis system of claim 7, wherein the data collection server determines and returns a plurality of data sub-packets based on the plurality of different tuples.
9. The data collection and analysis system of claim 1, wherein the data analysis server, after receiving the data sub-packet replied by the data collection server, determines whether the ID and time in the data sub-packet are the same as a binary group in the data acquisition request, and if the ID and time are the same as a binary group in the data acquisition request, the data sub-packet is correct, otherwise, the data sub-packet is incorrect.
10. The data collection and analysis system of claim 1, wherein the data analysis server determines to retain or delete the collected data it obtained according to a system security policy.
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