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 FP-Growth algorithms that can't timely find the latest crime and the serious crime, and then puts some improvements of the FP-Growth algorithms and tests it by carrying out experiments. Finally, it points out the future research aspect: extraction and correlation of multidimensional evidence.