Method for detecting integration of high-efficiency finegrained data

Abstract

The invention discloses a method for detecting the integration of high-efficiency finegrained data, relating to a method for detecting data integrity in the fields of data security and computer forensics. In the method, through encoding design based on the association and combination relation of lines and points in finite projective geometry, each supervision Hash corresponds to a point in a finite projective space, data objects to be supervised correspond to lines in the finite projective space, the point-line relation is utilized to determine the Hash supervision relation, multiple errors in a group of data objects can be accurately indicated, the compression rate is higher, the processing requirement of mass data can be met, and the storage space of Hash data and the network bandwidth required for Hash data transmission are saved. The method can be used for integration indication of forensic mapping in the computer forensics, and is applicable to integration detection of mass data,electronic data and computer evidences of data processing service department and judicial department, and also applicable to the occasions needing finegrained integration detection and fewer data error indication.

Description

technical field [0001] The invention relates to the field of data security in the subject of computer science and information security, in particular to a method for checking data integrity in the field of computer forensics. Background technique [0002] Use the one-way Hash function to generate the digital digest information of the data and store it. By regenerating the digital digest information of the data to be checked, and then comparing with the stored information, it is possible to check whether the data to be verified has changed, so as to realize the data integrity check— — If the digital summary information is not identical, the data has changed. The above-mentioned digital digest information is Hash data having a fixed length. The actual length of the digital digest information depends on the one-way Hash function used in the integrity check, and the length and the security of the Hash function itself have an impact on the security of the integrity check problem...

AI Technical Summary

Problems solved by technology

[0007] The first and second options will have the problems analyzed above, or the integrity inspection requirements are not met, or the Hash data scale is too large

The third option only implements a medium-grained integrity check that is larger than the fine-grained one, and does not meet the needs of integrity checks well.

[0011] The "complex rotation indicator code" proposed by Chen Long et al. in the paper "Fine-grained Data Integrity Indication Method Based on Complex Rotation Code" (Journal of Southwest Jiaotong University, 2009, Vol.44(5): 667-671) was realized for the first time It can accurately indicate multiple errors, and this code can achieve data compression of more than ten or twenty times. When the number of errors that need to be accurately indicated is slightly larger, the compression effect is poor

[0012] When the amount of data in forensics is not very large and the requirement for error indication ability is not high, the electronic evidence can be fixed by hypercube single error integrity indicator code; when the amount of data is relatively large but the requirement for error indication ability is not high, Combination of single error integrity indicator codes can be used to fix electronic evidence; when the amount of data in forensics is not very large but the error indication capability is high, complex rotation indicator codes can be used to fix electronic evidence; when the amount of data is large And when there is a high requirement for error indication capability, none of the existing fine-grained integrity indicator codes can meet this requirement

The actual cases of computer forensics are becoming more and more complex, and there have been cases involving hundreds of GB or even several TB of data. When it is necessary to process fine-grained massive data, the compression rate of the existing multi-error integrity indicator code can no longer meet the actual need

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