77 / 2015-12-21 14:21:37
Anomaly Detection of User Behavior for Database Security Audit Based on OCSVM
Security audit, user behavior, OCSVM, log preprocessing, anomaly detection
全文录用
Yong Li / State Grid Smart Grid Research Institute
Tao Zhang / State Grid Smart Grid Research Institute
YuanYuan Ma / State Grid Smart Grid Research Institute
Cheng Zhou / State Grid Smart Grid Research Institute
In view of the defects of Safety monitoring and comprehensive audit in information network boundaries of State Grid Corporation of China(SGCC), a kind of security audit technology based on One-Class support vector machine(OCSVM) is proposed for the security audit of user access behavior. Firstly, feature selection, syntax parsing of SQL statements and numerical processing of audit log are first completed to obtain the feature vector of user behavior, which can be trained and identified by OCSVM. Then the audit log that reflect the rules of normal behavior in the long-term operation of the database is used as the OCSVM's training input. After training, the OCSVM classifier is trained to build the pattern library of user behavior. Finally, the OCSVM classifier is used to detect the abnormal behavior of database operation, and to realize the security audit of database user access behavior.
重要日期
  • 会议日期

    05月21日

    2016

    05月22日

    2016

  • 10月30日 2015

    提前注册日期

  • 03月21日 2016

    初稿截稿日期

  • 04月01日 2016

    初稿录用通知日期

  • 04月10日 2016

    终稿截稿日期

  • 05月22日 2016

    注册截止日期

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亚利桑那州立大学
查尔斯特大学
重庆环球联合科学技术研究院
韦洛尔理工大学
阿尔托大学
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