• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

Computer Engineering & Science

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Survey on software vulnerability analysis
based on machine learning

KUANG Xiaohui1,LIU Qiang1,2 ,LI Xiang1,NIE Yuanping1   

  1. (1.National Key Laboratory of Science and Technology on Information System Security,
    Institute of System and Engineering,Academy of Military Science,Beijing 100101;
    2.Department of Computer Science and Technology,Tsinghua University,Beijing 100084,China)
  • Received:2018-03-12 Revised:2018-06-07 Online:2018-11-25 Published:2018-11-25

Abstract:

As increasing reporting and disclosure of vulnerability code samples and extensive applications of machine learning methods, software vulnerability analysis methods based on machine learning have become a hot research direction in information security. After analysis of existing research work, we propose a software vulnerability analysis framework based on machine learning. We then review and classify existing machine learning based vulnerability methods, and conduct comparative analysis. We briefly analyze the challenges for machine learning based software vulnerability analysis methods, and discuss future research trends.
 

Key words: software vulnerability analysis, machine learning, survey