CN113127881A - Data security processing method based on big data - Google Patents
Data security processing method based on big data Download PDFInfo
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- CN113127881A CN113127881A CN202110421989.3A CN202110421989A CN113127881A CN 113127881 A CN113127881 A CN 113127881A CN 202110421989 A CN202110421989 A CN 202110421989A CN 113127881 A CN113127881 A CN 113127881A
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- G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
- G06F21/57—Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
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Abstract
The invention discloses a data security processing method based on big data, which comprises the following steps: step one, generating a secret key; step two, constructing a model; step three, optimizing the model; step four, data acquisition; step five, data encryption; step six, data decryption; according to the invention, the acquired data is processed by using a public key encryption method, so that the risk of malicious stealing and tampering of the data in the transmission process is reduced, the usability, integrity and confidentiality of the data are ensured, the circulation safety of the data is ensured, a security vulnerability analysis model is constructed by using big data, the data is comprehensively analyzed for security vulnerabilities, and a proper encryption method is matched, so that the security vulnerability range aimed by the encryption method is expanded, the encryption effect of the encryption method is improved, the data is prevented from being damaged, changed and leaked due to unknown security vulnerabilities, the application range is wide, the reliability is strong, the confidentiality grade is high, and the security risk of the data is reduced.
Description
Technical Field
The invention relates to the technical field of big data processing, in particular to a data security processing method based on big data.
Background
The data security processing is realized by adopting various security protection technologies as the name implies, so that the problems of increase, modification, loss, leakage and the like of data in the processes of acquisition, storage, retrieval, processing, transformation and transmission can be avoided, the usability, integrity and confidentiality of the data are ensured, and the circulation security of the data is ensured.
However, most of the traditional data security processing methods do not encrypt the acquired data, the data is easily stolen and tampered maliciously in the transmission process, the usability, integrity and confidentiality of the data are damaged, the circulation security of the data is influenced, a few of the traditional data security processing methods are encrypted, the encryption method can be selected only according to the locally known data security vulnerability, the targeted security vulnerability range is limited, the encryption effect is insufficient, when the locally unknown data security vulnerability is met, the data is easily damaged, changed and leaked in the processing process, the application range is small, the reliability is poor, the confidentiality level is low, and certain potential safety hazards exist.
Therefore, it is necessary to design a data security processing method based on big data.
Disclosure of Invention
The present invention is directed to a data security processing method based on big data, so as to solve the problems mentioned in the background art.
In order to solve the technical problems, the invention provides the following technical scheme: a data security processing method based on big data comprises the following steps: step one, generating a secret key; step two, constructing a model; step three, optimizing the model; step four, data acquisition; step five, data encryption; step six, data decryption;
in the first step, the data cloud end screens out a large amount of original data with corresponding characteristics, security holes of the original data and available encryption methods of the security holes from the big data according to the characteristics of the data to be processed, and generates corresponding key pairs according to different encryption methods;
in the second step, the original data obtained in the first step is divided into training set data and test set data, and the training set data and the security loophole and encryption method obtained in the first step are subjected to logic calculation by using a decision tree algorithm to construct an original analysis model;
in the third step, the test set data obtained in the second step is substituted into the original analysis model obtained in the second step, the quality of the judgment result of the original analysis model is evaluated through the evaluation index, and the security vulnerability analysis model is obtained through a cost complexity pruning method;
in the fourth step, the data terminal closes the conventional input program, starts the safe input program, guides the user to perform data input operation, and obtains input data after the data terminal finishes the acquisition;
in the fifth step, the data terminal calls a security vulnerability analysis model obtained by the data cloud from the third step, performs security vulnerability analysis on the input data obtained in the fourth step, judges a key pair matched with the input data according to the key pair obtained in the first step, and encrypts the input data through a public key in the key pair to obtain encrypted data;
in the sixth step, the data terminal uploads the encrypted data obtained in the fifth step to the data cloud end through the encryption network, and the data cloud end decrypts the encrypted data through the private key in the key pair to obtain decrypted data.
According to the technical scheme, in the first step, the key pair consists of an encryption public key and a decryption private key, and the encryption public key and the decryption private key are respectively stored in the data terminal and the data cloud.
According to the above technical solution, in the second step, the training set data and the test set data respectively account for 70% and 30% of the original data.
According to the technical scheme, in the second step, the decision tree algorithm is a classification regression decision tree algorithm.
According to the technical scheme, in the third step, the evaluation indexes are four items of accuracy, recall ratio, precision ratio and AUC value.
According to the technical scheme, in the third step, the branch with bad judgment result in the decision tree of the original analysis model is cut by the cost complexity pruning method, and then the trunk with good judgment result in the decision tree of the original analysis model is reserved.
According to the technical scheme, in the fifth step, the security vulnerability analysis firstly obtains a plurality of encryption methods which are available for all security vulnerabilities of the input data, an optimal encryption method which is a mapping collection is preferably selected, and then key pair matching is carried out on the optimal encryption method.
Compared with the prior art, the invention has the following beneficial effects: according to the data security processing method based on the big data, the collected data is processed by using a public key encryption method, so that the risks of malicious stealing and tampering of the data in the transmission process are reduced, the usability, integrity and confidentiality of the data are ensured, and the circulation security of the data is ensured; the security vulnerability analysis model is constructed by utilizing big data, scientific support is provided for the encryption method, the security vulnerability range aimed by the encryption method is expanded, the encryption effect of the encryption method is improved, the data is prevented from being damaged, changed and leaked due to unknown security vulnerabilities, the application range is wide, the reliability is high, the confidentiality level is high, and the security risk of the data is reduced; the security vulnerability analysis model is optimized through a cost complexity pruning method, so that the quality of the security vulnerability analysis model is improved, the accuracy, the recall ratio, the precision ratio and the AUC value of the security vulnerability analysis model are improved, the security of the encryption method is enhanced, and the circulation security of data is ensured.
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 flow chart of the method of 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 derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the present invention provides a technical solution: a data security processing method based on big data comprises the following steps: step one, generating a secret key; step two, constructing a model; step three, optimizing the model; step four, data acquisition; step five, data encryption; step six, data decryption;
in the first step, the data cloud end screens out a large amount of original data with corresponding characteristics, security holes of the original data and available encryption methods of the security holes from the big data according to the characteristics of the data to be processed, and generates corresponding key pairs according to different encryption methods, wherein the key pairs consist of an encryption public key and a decryption private key, and the encryption public key and the decryption private key are respectively stored in the data terminal and the data cloud end;
in the second step, the original data obtained in the first step is divided into training set data and test set data, the training set data and the test set data respectively account for 70% and 30% of the original data, logic calculation is carried out on the training set data and the security loophole and encryption method obtained in the first step by using a decision tree algorithm, and a classification regression decision tree algorithm is selected for the decision tree algorithm to construct an original analysis model;
in the third step, the test set data obtained in the second step is substituted into the original analysis model obtained in the second step, the quality of the judgment result of the original analysis model is evaluated through evaluation indexes, the evaluation indexes are four items of accuracy, recall ratio, precision ratio and AUC value, a security vulnerability analysis model is obtained through a cost complexity pruning method, branches with bad judgment result in a decision tree of the original analysis model are firstly pruned through the cost complexity pruning method, and then the branches with good judgment result in the decision tree of the original analysis model are reserved;
in the fourth step, the data terminal closes the conventional input program, starts the safe input program, guides the user to perform data input operation, and obtains input data after the data terminal finishes the acquisition;
in the fifth step, the data terminal calls a security vulnerability analysis model obtained by the data cloud from the third step, security vulnerability analysis is carried out on the input data obtained in the fourth step, a plurality of encryption methods available for all security vulnerabilities of the input data are obtained firstly through the security vulnerability analysis, an optimal encryption method which is a mapping collection is selected, then key pair matching is carried out on the optimal encryption method, a key pair matched with the input data is judged according to the key pair obtained in the first step, and the input data are encrypted through a public key in the key pair to obtain encrypted data;
in the sixth step, the data terminal uploads the encrypted data obtained in the fifth step to the data cloud end through the encryption network, and the data cloud end decrypts the encrypted data through the private key in the key pair to obtain decrypted data.
Based on the above, the invention has the advantages that the invention uses the public key encryption method to process the acquired data, thereby reducing the risk of malicious stealing and tampering of the data in the transmission process, ensuring the usability, integrity and confidentiality of the data, ensuring the circulation safety of the data, and using big data to construct a security vulnerability analysis model, providing scientific support for the encryption method, thereby expanding the security vulnerability range aimed by the encryption method, improving the encryption effect of the encryption method, preventing the data from being damaged, changed and leaked due to unknown security vulnerabilities, having wide application range, strong reliability, high confidentiality grade and reducing the security risk of the data.
It is noted that, herein, relational terms such as first and second, and the like may be 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 (7)
1. A data security processing method based on big data comprises the following steps: step one, generating a secret key; step two, constructing a model; step three, optimizing the model; step four, data acquisition; step five, data encryption; step six, data decryption; the method is characterized in that:
in the first step, the data cloud end screens out a large amount of original data with corresponding characteristics, security holes of the original data and available encryption methods of the security holes from the big data according to the characteristics of the data to be processed, and generates corresponding key pairs according to different encryption methods;
in the second step, the original data obtained in the first step is divided into training set data and test set data, and the training set data and the security loophole and encryption method obtained in the first step are subjected to logic calculation by using a decision tree algorithm to construct an original analysis model;
in the third step, the test set data obtained in the second step is substituted into the original analysis model obtained in the second step, the quality of the judgment result of the original analysis model is evaluated through the evaluation index, and the security vulnerability analysis model is obtained through a cost complexity pruning method;
in the fourth step, the data terminal closes the conventional input program, starts the safe input program, guides the user to perform data input operation, and obtains input data after the data terminal finishes the acquisition;
in the fifth step, the data terminal calls a security vulnerability analysis model obtained by the data cloud from the third step, performs security vulnerability analysis on the input data obtained in the fourth step, judges a key pair matched with the input data according to the key pair obtained in the first step, and encrypts the input data through a public key in the key pair to obtain encrypted data;
in the sixth step, the data terminal uploads the encrypted data obtained in the fifth step to the data cloud end through the encryption network, and the data cloud end decrypts the encrypted data through the private key in the key pair to obtain decrypted data.
2. The big data based data security processing method according to claim 1, wherein: in the first step, the key pair consists of an encryption public key and a decryption private key, and the encryption public key and the decryption private key are respectively stored in the data terminal and the data cloud.
3. The big data based data security processing method according to claim 1, wherein: in the second step, the training set data and the test set data respectively account for 70% and 30% of the original data.
4. The big data based data security processing method according to claim 1, wherein: in the second step, the decision tree algorithm is a classification regression decision tree algorithm.
5. The big data based data security processing method according to claim 1, wherein: in the third step, the evaluation indexes are four items of correct rate, recall ratio, precision ratio and AUC value.
6. The big data based data security processing method according to claim 1, wherein: in the third step, the cost complexity pruning method firstly prunes the branches with bad judgment results in the decision tree of the original analysis model, and then reserves the trunks with good judgment results in the decision tree of the original analysis model.
7. The big data based data security processing method according to claim 1, wherein: in the fifth step, the security vulnerability analysis firstly obtains a plurality of encryption methods which are available for all security vulnerabilities of the input data, an optimal encryption method which is a mapping collection is preferably selected, and then key pair matching is carried out on the optimal encryption method.
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