一种基于程序切片相似度匹配的脆弱性发现方法

doi:10.11896/j.issn.1002-137X.2019.07.020

Abstract

Abstract: Vulnerability analysis method based on similarity matching is one of the most effective vulnerability analysis methods.How to reduce the false positive rate without reducing the false negative rate,and increase the efficiency,are the main goals to optimize the method.Aiming at these challenges,this paper proposed an optimization vulnerability analysis framework based on similarity matching of program slices.In the framework,the methods of code slice,feature extraction and vectorization based on vulnerable key points were studied.The core ideal of the framework is taking vulnerability semantic context slice of the vulnerability code as a reference to calculate the similarity between the slice of the tested code and the vulnerable sample slice,and determining the likelihood of a vulnerability.This paper implemented this framework and validateed it with open source projects with known vulnerabilities.Compared with the existing research,the vulnerability slice similarity framework has the ability to close describe the vulnerability context,and the vulnerability discovery method based on similarity matching is optimized by the slice technique.The proposed framework and method are verified to effectively reduce the false positive rate and false negative rate ofvulnerabi-lity discovery.

Key words: Programing slicing, Similarity matching, Vulnerability analysis

CLC Number:

TP393

LIU Qiang,KUANG Xiao-hui,CHEN Hua,LI Xiang,LI Guang-ke. Vulnerability Discovery Approach Based on Similarity Matching of Program Slicing[J].Computer Science, 2019, 46(7): 126-132.

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Vulnerability Discovery Approach Based on Similarity Matching of Program Slicing

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