CN115378680A - Electronic chip information encryption system and method based on big data - Google Patents
Electronic chip information encryption system and method based on big data Download PDFInfo
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Abstract
The invention discloses an electronic chip information encryption system and method based on big data, wherein the system comprises a data acquisition module, an information processing module, a database module and a data encryption module; the data acquisition module is used for acquiring information data stored in the electronic chip and transmitting all the acquired data to the database; the information processing module is used for carrying out security test on the acquired storage information in the electronic chip and judging whether the acquired information contains privacy or sensitive information; the database module is used for storing all the acquired information data; the data encryption module is used for encrypting data containing private or sensitive information; the system and the method realize the safety monitoring of the process of collecting the information stored in the electronic chip, judge whether the collected data contains privacy or sensitive information, and avoid the leakage of the core information of the electronic chip.
Description
Technical Field
The invention relates to the technical field of electronic chip information encryption, in particular to an electronic chip information encryption system and method based on big data.
Background
Along with the development of the mobile internet, intelligent hardware serving as a carrier plays a key role in the development, information exchange and transmission are independent of a hardware terminal, an electronic chip serving as one of the cores of the intelligent hardware bears important functions and stores information and data of people, communication and exchange of the people are facilitated, and important contribution is made to the development of life and society of the people; meanwhile, chip core information containing privacy or sensitive information is leaked in the information exchange and transmission process, so that the information encryption technology is a core technology for guaranteeing the information security of the electronic chip, the information transmission security can be improved to a certain extent through the information encryption technology, and the data transmission integrity is guaranteed. The invention provides an electronic chip information encryption system and method based on big data, and solves the technical problem that an existing electronic chip is low in safety.
Disclosure of Invention
The invention aims to provide an electronic chip information encryption system and method based on big data, so as to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: an electronic chip information encryption system based on big data, the system comprising: the system comprises a data acquisition module, an information processing module, a database module and a data encryption module; the data acquisition module is used for acquiring information data stored in the electronic chip and transmitting all the acquired data to the database; the information processing module is used for carrying out security test on the acquired storage information in the electronic chip and judging whether the acquired information contains privacy or sensitive information; the database module is used for storing all the acquired information data; the data encryption module is used for encrypting data containing private or sensitive information.
Furthermore, the information processing module comprises a risk monitoring unit and a safety analysis unit, wherein the risk monitoring unit is used for monitoring whether the stored information acquisition process of the electronic chip has a leakage risk or not and timely controlling the possible risk; the safety analysis unit is used for analyzing the collected storage information of the electronic chip, selecting data containing privacy or sensitive information for classification, and uploading the classified data to the database module.
Further, the database module comprises a first storage unit and a second storage unit, wherein the first storage unit is used for storing information data stored by the electronic chip which does not contain privacy or sensitive information; the second storage unit is used for storing electronic chip storage information data containing privacy or sensitive information; and the database module is connected with the data encryption module and is used for the data encryption module to access and acquire data containing privacy or sensitive information.
Further, the data encryption module comprises an information encryption unit and a safety control unit, wherein the information encryption unit is used for accessing the database module, acquiring data containing privacy or sensitive information, and encrypting the data; and the safety control unit is used for controlling the data stored in the acquisition database module in real time and preventing requests for acquiring data containing privacy and sensitive information.
An electronic chip information encryption method based on big data comprises the following steps:
s1: collecting information stored on an electronic chip, and carrying out risk monitoring on the collection process;
s2: classifying the acquired information into information containing privacy and sensitive information and information not containing privacy and sensitive information;
s3: encrypting data containing private and sensitive information;
s4: and monitoring the request for acquiring the data in the database in real time, and preventing the behavior of acquiring the data containing the privacy and sensitive information.
Further, in step S1: the method comprises the steps of monitoring the process of collecting information stored in an electronic chip in real time, wherein the number of times of collecting the information stored in the electronic chip is n, the number set of the collected information at each time is F = { F1, F2, \8230;, fn }, and the number set of the information checked in the collected information is A = { A1, A2, \8230;, am }, wherein m represents the number of the information in the process of collecting at one time, and the safety degree Yi in the process of collecting the information of the electronic chip is calculated according to the following formula:
the method comprises the steps of obtaining a set of safety degrees in the process of acquiring the information of the electronic chip, wherein the safety degrees are Y = { Y1, Y2, \8230;, yn }, carrying out straight line fitting on data points { (1, Y1), (2, Y2), \8230; (n, yn) } according to a least square method to obtain a fitting function of Y = ax + b, wherein a and b represent fitting coefficients, substituting the data points into the fitting function, setting a risk threshold value of ai + b, wherein i represents the times of acquiring the information of the electronic chip, and i =1, 2.., n, and comparing ai + b with Yi: if Yi- (ai + b) <0, it indicates that the security degree is lower than the threshold value in the process of acquiring the electronic chip information corresponding to Yi, at this moment, information leakage risks may exist in the acquisition process, acquisition needs to be stopped, and whole-process monitoring is realized in the process of acquiring the electronic chip information by using the security degree function, so that the core information of the electronic chip is prevented from being leaked before being encrypted.
Further, in step S2: before encrypting collected electronic chip information, the information is firstly classified, data containing privacy or sensitive information is classified into one class, a word frequency TF technology is firstly utilized to obtain key words, and the formula is as follows: TF w Number of occurrences of an entry in a class/number of entries in the class, where TF w Judging the privacy and sensitivity of the keywords for the occurrence frequency of the keywords, and finally generating a privacy and sensitive keyword set; classifying information according to privacy and sensitive keywords, wherein the classification method utilizes a naive Bayes method, firstly determines the keywords as characteristic attributes, appropriately divides each characteristic attribute to form a training sample set, then calculates the occurrence frequency of each category in the training sample and the conditional probability estimation of each category by dividing each characteristic attribute, records the result, and finally divides the recorded result into data containing the privacy and sensitive information and data not containing the privacy and sensitive information; the electronic chip information is classified, the information encryption process is greatly simplified, the encrypted information is more targeted, and the information encryption efficiency is improved.
Further, in step S3: selecting classified data containing privacy and sensitive word information, encrypting the data by using an MD5 algorithm, firstly processing an original text, wherein the length of one character is 8 bits, calculating the length of the original text, then solving the length of the original text for a remainder result of 512, if the length of the original text is not equal to 448, filling the original text in a mode that the remainder result of 512 of the original text is 448, wherein the filling method comprises the steps of filling 1 in the first bit and filling 0 in the rest bits; after filling, the information length is 512 × N +448, and N is the packet number of the original text in one packet per 512 bits; then, recording the real length of the original text at the position of the remaining 512-448=64 bits, and finally filling the binary value of the length, wherein the length of the message processed finally is 512 × n1; then, an initial value is set, the length of the hash result of MD5 is 128 bits, 4 packets are grouped by a total of 32 bits, and 4 initial values a, B, C, and D are set for the results of the four packets, and then four nonlinear functions are set:
F(X,Y,Z)＝(X&Y)|((～X)&Z)
G(X,Y,Z)＝(X&Z)|(Y&(～Z))
H(X,Y,Z)＝X^Y^Z
I(X,Y,Z)＝Y^(X|(～Z))
and, | is or, -is not, ^ is exclusive or, the description of these four functions: if the corresponding bits of X, Y and Z are independent and uniform, then each bit of the result should also be independent and uniform; then processing the data segment, processing the input message operation by taking 512-bit data segment as a unit, performing 4 rounds of logic processing on each data segment, and respectively using four nonlinear functions F, G, H and I in 4 rounds; the ABCD and the current 512-bit block are used as input in each round, and the ABCD is sent to be 128 after processing; finally, splicing the result, namely splicing four values A, B, C and D finally generated by circular processing together, and converting the four values into character strings; after the classified data containing the privacy and sensitive word information is encrypted through the MD5 algorithm, the risk of euphoria leakage of the data in the processes of transmission and acquisition is avoided, and the privacy safety of chip information is greatly improved.
Further, in step S4: for better protection of data containing private or sensitive information, although the data has been encrypted in step S3, a further barrier is added during the access to the data stored in the database module, the requests for access to and for data in the database module are monitored in real time and blocked against requests for data containing private or sensitive information.
Compared with the prior art, the invention has the following beneficial effects: the information stored in the electronic chip is encrypted based on big data, wherein the data acquisition module is used for acquiring the information of the electronic chip, the information processing module monitors the acquisition process in real time, a safety degree equation is established to control the possible leakage risk in the acquisition process, meanwhile, the acquired data is judged through a word frequency TF technology and a naive Bayesian method to determine whether the acquired data contains privacy or sensitive information, the acquired data is divided into data containing the privacy or sensitive information and data not containing the privacy or sensitive information, and then the data encryption module encrypts the data containing the privacy or sensitive information by using an MD5 algorithm to avoid the leakage of the core information of the electronic chip.
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 specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic diagram of a big data-based electronic chip information encryption system according to the present invention;
FIG. 2 is a schematic flow chart of an electronic chip information encryption method based on big data according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Referring to fig. 1-2, the present invention provides a technical solution: an electronic chip information encryption system based on big data, the system comprising: the system comprises a data acquisition module, an information processing module, a database module and a data encryption module; the data acquisition module is used for acquiring information data stored in the electronic chip and transmitting all the acquired data to the database; the information processing module is used for carrying out security test on the collected storage information in the electronic chip and judging whether the collected information contains privacy or sensitive information; the database module is used for storing all the acquired information data; the data encryption module is used for encrypting data containing privacy or sensitive information.
The information processing module comprises a risk monitoring unit and a safety analysis unit, wherein the risk monitoring unit is used for monitoring whether the leakage risk exists in the process of acquiring the stored information of the electronic chip; the safety analysis unit is used for analyzing the acquired storage information of the electronic chip and selecting data containing privacy or sensitive information for classification.
The database module comprises a first storage unit and a second storage unit, wherein the first storage unit is used for storing the storage information of the electronic chip which does not contain privacy or sensitive information; the second storage unit is used for storing electronic chip storage information containing privacy or sensitive information.
The data encryption module comprises an information encryption unit and a security management and control unit, wherein the information encryption unit is used for encrypting data containing privacy or sensitive information; and the safety control unit is used for controlling the data stored in the acquisition database module in real time and preventing requests for acquiring data containing privacy and sensitive information.
An electronic chip information encryption method based on big data comprises the following steps:
s1: collecting information stored on an electronic chip, and carrying out risk monitoring on the collection process;
s2: classifying the collected information into information containing privacy and sensitive information and information not containing privacy and sensitive information;
s3: encrypting data containing private and sensitive information;
s4: and monitoring the request for acquiring the data in the database in real time, and preventing the behavior of acquiring the data containing the privacy and sensitive information.
In step S1: the method comprises the steps of monitoring the process of collecting information stored in an electronic chip in real time, monitoring the number of times of collecting the information stored in the electronic chip to be n, wherein the number set of the information collected each time is F = { F1, F2, \8230;, fn }, and the number set of the information viewed in the collected information is A = { A1, A2, \8230;, am }, wherein m represents the number of the information in the process of collecting one time, and calculating the safety degree Yi in the process of collecting the information of the electronic chip according to the following formula:
the method comprises the steps of obtaining a set of safety degrees in the process of acquiring the information of the electronic chip, wherein the safety degrees are Y = { Y1, Y2, \8230;, yn }, carrying out straight line fitting on data points { (1, Y1), (2, Y2), \8230; (n, yn) } according to a least square method to obtain a fitting function of Y = ax + b, wherein a and b represent fitting coefficients, substituting the data points into the fitting function, setting a risk threshold value of ai + b, wherein i represents the times of acquiring the information of the electronic chip, and i =1, 2.., n, and comparing ai + b with Yi: if Yi- (ai + b) <0, it indicates that the security degree is lower than the threshold value in the process of acquiring the electronic chip information corresponding to Yi, at this moment, the risk of information leakage may exist in the acquisition process, acquisition needs to be stopped, and the whole-process monitoring is realized on the process of acquiring the electronic chip information by using the security degree function, so that the core information of the electronic chip is prevented from being leaked before being encrypted.
In step S2: before encrypting collected electronic chip information, classifying the information, dividing data containing privacy or sensitive information into a class, and acquiring keywords by using a word frequency (TF) technology, wherein the formula is as follows: TF w Number of occurrences of an entry in a class/number of entries in the class, where TF w Judging the privacy and sensitivity of the keywords for the occurrence frequency of the keywords, and finally generating a privacy and sensitive keyword set; classifying information according to privacy and sensitive keywords, wherein the classification method uses a naive Bayes method, firstly, the keywords are determined as characteristic attributes, each characteristic attribute is appropriately divided to form a training sample set, and then, each category is calculated in trainingThe occurrence frequency and each characteristic attribute in the sample are divided into the conditional probability estimation of each category, the result is recorded, and finally the recorded result is divided into data containing privacy and sensitive information and data not containing privacy and sensitive information; the electronic chip information is classified, the information encryption process is greatly simplified, the encrypted information is more targeted, and the information encryption efficiency is improved.
In step S3: selecting classified data containing privacy and sensitive word information, encrypting the data by using an MD5 algorithm, firstly processing an original text, wherein the length of one character is 8 bits, calculating the length of the original text, then solving the length of the original text for a remainder result of 512, if the length of the original text is not equal to 448, filling the original text in a mode that the remainder result of 512 of the original text is 448, wherein the filling method comprises the steps of filling 1 in the first bit and filling 0 in the rest bits; after filling, the information length is 512 × N +448, and N is the packet number of the original text in one packet per 512 bits; then, recording the real length of the original text at the position of the remaining 512-448=64 bits, and finally filling the binary value of the length, wherein the length of the message processed finally is 512 × n1; then, an initial value is set, the length of the hash result of MD5 is 128 bits, 4 packets are grouped by a total of 32 bits, and 4 initial values a, B, C, and D are set for the results of the four packets, and then four nonlinear functions are set:
F(X,Y,Z)＝(X&Y)|((～X)&Z)
G(X,Y,Z)＝(X&Z)|(Y&(～Z))
H(X,Y,Z)＝X^Y^Z
I(X,Y,Z)＝Y^(X|(～Z))
and is AND, | is OR, -is not, ^ is exclusive-OR, and the description of the four functions: if the corresponding bits of X, Y and Z are independent and uniform, then each bit of the result should also be independent and uniform; then processing the data segment, processing the input message operation by taking 512-bit data segment as a unit, performing 4 rounds of logic processing on each data segment, and respectively using four nonlinear functions F, G, H and I in 4 rounds; the ABCD and the current 512-bit block are used as input in each round, and the processed ABCD is sent to 128; finally, splicing the results, namely splicing four values A, B, C and D finally generated by circular processing together and converting the four values into character strings; after the classified data containing the privacy and sensitive word information is encrypted through the MD5 algorithm, the risk of euphoria leakage of the data in the processes of transmission and acquisition is avoided, and the privacy safety of chip information is greatly improved.
In step S4: for better protection of data containing private or sensitive information, although the data has been encrypted in step S3, a further barrier is added during the access to the data stored in the database module, the requests for access to and for data in the database module are monitored in real time and blocked against requests for data containing private or sensitive information.
The first embodiment is as follows: monitoring the process of collecting information stored on an electronic chip three times, wherein the set of the quantity of the information collected each time is F = { F1, F2, F3} = {10, 10, 15}, and the set of the quantity of the information to be checked in the information collected at one time randomly is A = { A1, A2, A3} = {9,8,9}, according to a formula
Calculating the safety degree Y1=12, obtaining a safety degree set of Y = { Y1, Y2, Y3} = {12, 11, 10}, performing straight line fitting on data points { (1, Y1), (2, Y2), (3, Y3) } by using a least square method, obtaining a fitting function of Y = ax + b =3x +4, substituting the data points into the fitting function, setting a safety degree threshold value as ai + b, and comparing ai + b with Yi: y1- (a 1 b)>0；Y2-(a*2+b)>0；Y3-(a*3+b)>0, the acquired stored information of the electronic chip each time is acquired, and no leakage risk exists in the acquisition process; acquiring a keyword address from the acquired information by using a word frequency TF technology, determining the address as a characteristic attribute by using a naive Bayes method, and dividing the address into data containing the address; selecting data containing an address, encrypting the data by using an MD5 algorithm to obtain 4 initial values, namely A =0x67452301, B =0xefcdab89, C =0x98badcfe, D =0x10325476; then according to a non-linear function F (X, Y, Z) = (X)&Y)|((～X)&Z)、G(X,Y,Z)＝(X&Z)|(Y&(～Z))、H(X,Y,Z)＝X^Y^Z、I (X, Y, Z) = Y ^ (X | (-Z)) to carry out cyclic processing, and finally MD5 ("address") =900150983cd24fb0d6963f7 e17f72 is obtained;
it should be noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. An electronic chip information encryption system based on big data, characterized in that the system comprises: the system comprises a data acquisition module, an information processing module, a database module and a data encryption module; the data acquisition module is used for acquiring information data stored in the electronic chip and transmitting all the acquired data to the database; the information processing module is used for carrying out security test on the collected storage information in the electronic chip and judging whether the collected information contains privacy or sensitive information; the database module is used for storing all the acquired information data; the data encryption module is used for encrypting data containing private or sensitive information.
2. The big data based electronic chip information encryption system according to claim 1, wherein: the information processing module comprises a risk monitoring unit and a safety analysis unit, wherein the risk monitoring unit is used for monitoring whether the leakage risk exists in the process of acquiring the stored information of the electronic chip; the safety analysis unit is used for analyzing the acquired storage information of the electronic chip and selecting data containing privacy or sensitive information for classification.
3. The big data based electronic chip information encryption system as claimed in claim 1, wherein: the database module comprises a first storage unit and a second storage unit, wherein the first storage unit is used for storing data of the storage information of the electronic chip which does not contain privacy or sensitive information; the second storage unit is used for storing data of electronic chip storage information containing privacy or sensitive information; and the database module is connected with the data encryption module and is used for the data encryption module to access and acquire data containing privacy or sensitive information.
4. The big data based electronic chip information encryption system as claimed in claim 1, wherein: the data encryption module comprises an information encryption unit and a safety control unit, wherein the information encryption unit is used for accessing the database module, acquiring data containing privacy or sensitive information and encrypting the data; and the safety control unit is used for monitoring and acquiring the access request of the storage data in the database module in real time.
5. An electronic chip information encryption method based on big data is characterized by comprising the following steps:
s1: collecting information stored on an electronic chip, and carrying out risk monitoring on the collection process;
s2: classifying the acquired information into information containing privacy and sensitive information and information not containing privacy and sensitive information;
s3: encrypting data containing privacy and sensitive information;
s4: and monitoring the request for acquiring the data in the database in real time, and preventing the behavior of acquiring the data containing the privacy and sensitive information.
6. The big data-based electronic chip information encryption method according to claim 5, wherein in step S1: the method comprises the steps of monitoring the number of times of collecting information stored on an electronic chip to be n, wherein the number set of the collected information at each time is F = { F1, F2, \8230;, fn }, monitoring the number set of the information checked in the information collected at one time randomly to be A = { A1, A2, \8230;, am }, wherein m represents the number of the information in the process of collecting at one time randomly, and calculating the safety degree Yi in the process of collecting the information of the electronic chip according to the following formula:
the method comprises the steps of obtaining a safety degree set in the process of acquiring information of the electronic chip, wherein the safety degree set is Y = { Y1, Y2, \8230;, yn }, carrying out straight line fitting on data points { (1, Y1), (2, Y2), \8230; (n, yn) } according to a least square method to obtain a fitting function of Y = ax + b, wherein a and b represent fitting coefficients, substituting the data points into the fitting function, setting a risk threshold value to be ai + b, and comparing ai + b with Yi: if Yi- (ai + b) <0, it indicates that the safety degree is lower than the threshold value in the process of acquiring the electronic chip information corresponding to Yi, at this time, there is a risk of information leakage in the acquisition process, and acquisition needs to be stopped, wherein i represents the number of times of acquiring the electronic chip information, and i =1, 2.
7. The big data-based electronic chip information encryption method according to claim 5, wherein in step S2: the method comprises the steps of acquiring keywords from collected information by using a word frequency TF technology, judging the privacy and sensitivity of the keywords, generating a privacy and sensitivity keyword set, determining the keywords as feature attributes by using a naive Bayes method, and dividing the keywords into data containing privacy and sensitivity information and data not containing privacy and sensitivity information.
8. The big data-based electronic chip information encryption method according to claim 5, wherein in step S3: selecting data containing privacy and sensitive word information, encrypting the data by using an MD5 algorithm, 1, processing an original text, wherein the length of one character is 8 bits, calculating the number of the bits of the original text, then obtaining the result of the length of the original text for remainder 512, if the result of the length of the original text for remainder is not equal to 448, filling the original text in a mode that the result of the remainder of the original text for remainder 512 is 448, wherein the filling method is to fill 1 in the first bit and fill 0 in the rest bits; after filling, the information length is 512 × N +448, and N is the packet number of the original text in one packet per 512 bits; then, recording the real length of the original text at the position of the remaining 512-448=64 bits, and finally filling the binary value of the length, wherein the length of the message processed finally is 512 × n1; 2. setting an initial value, wherein the length of a hash result of MD5 is 128 bits, and 4 groups are grouped according to 32 bits; the results of the four groups are set with 4 initial values A, B, C and D; then, four non-linear functions are set:
F(X,Y,Z)＝(X&Y)|((～X)&Z)
G(X,Y,Z)＝(X&Z)|(Y&(～Z))
H(X,Y,Z)＝X^Y^Z
I(X,Y,Z)＝Y^(X|(～Z))
and, | is or, -is not, ^ is exclusive or, the description of these four functions: if the corresponding bits of X, Y and Z are independent and uniform, then each bit of the result should also be independent and uniform; 3. processing data segments, namely processing the input message operation by taking 512-bit data segments as units, performing 4 rounds of logic processing on each data segment, and respectively using four nonlinear functions F, G, H and I in 4 rounds; the ABCD and the current 512-bit block are used as input in each round, and the ABCD is sent to be 128 after processing; 4. and splicing the four values A, B, C and D finally generated by the circular processing into a character string.
9. The big data based electronic chip information encryption method according to claim 5, wherein in step S4: requests to access and retrieve data stored in the database module are monitored in real time for which requests to retrieve data containing private and sensitive information are to be blocked.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117061189A (en) * | 2023-08-26 | 2023-11-14 | 上海六坊信息科技有限公司 | Data packet transmission method and system based on data encryption |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117061189A (en) * | 2023-08-26 | 2023-11-14 | 上海六坊信息科技有限公司 | Data packet transmission method and system based on data encryption |
| CN117061189B (en) * | 2023-08-26 | 2024-01-30 | 上海六坊信息科技有限公司 | Data packet transmission method and system based on data encryption |
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