Dynamic Credibility Detection Model Base on Scene Mining for Software Behavior

摘要：

Most of the current detection models for software behavior focus on the integrity detecting of its running path, but they rarely consider detecting the function realization integrity in each stage of the software running path. Therefore, dynamic credibility detection model based on scene mining for software behavior called SCDM is proposed in this paper. First of all, this model describes the integrity of various stages function implementation by introducing the concept of scene. Secondly, the model used association rules and sequence pattern algorithm in scene mining. Both of the algorithms can extract the hidden and valuable association information from the captured scene information set And the mining result is used for credibility detection of software behavior. Finally, the results of simulation experiments indicate that CDMBSM model has a good detection performance.

关键词： software behavior scene association rules sequence pattern

作者: Junfeng Tian Yatao Wang Xinling Li

作者单位: College of Mathematics and Computer Science HeBei University Baoding, Hebei, PR China Network Management Center Xingtai Branch of China Unicom Xingtai, Hebei, PR China

会议类型: 国际会议

会议名称: 2010 International Conference on Information Security and Artificial Intelligence(2010年信息安全与人工智能国际会议 ISAI 2010)

会议地点: 成都

会议语种:英文

页码: 828-832

在线出版日期: 2010-12-17（万方平台首次上网日期，不代表论文的发表时间）