Applications of Association Rules in Computer Crime Forensics

摘要：

Association rules can mine the relevant evidence of computer crime from the mass of data and association rules among data items, and further mine crime laws, trends and connections among different crimes. It provides police’s case detection and crime prevention with clues and criterions. This paper firstly analyzes the application of FP-Growth algorithms in computer crime forensics, points out the defect of FPGrowth algorithms that can’t timely find the latest crime and the serious crime, and then puts some improvements of the FPGrowth algorithms and tests it by carrying out experiments. Finally, it points out the future research aspect: extraction and correlation of multidimensional evidence.

关键词： data mining computer crime forensics association rules fp-growth

作者: Yuesheng Tan Zhansheng Qi Jingyu Wang

作者单位: Information and Network CenterInner Mongolia University of Science &TechnologyBaotou, China Information and Network Center Inner Mongolia University of Science &Technology Baotou, China

会议类型: 国际会议

会议名称: 2011 International Conference on Information System and Computational Intelligence(2011 IEEE信息系统与计算智能国际会议 ICISCI 2011)

会议地点: 哈尔滨

会议语种:英文

页码: 91-94

在线出版日期: 2011-01-18（万方平台首次上网日期，不代表论文的发表时间）