A Log Analysis Technology Based on FP-growth Improved Algorithm
Jin Bo Chen, Wenyu Hu, KangHui Ying, Guo Nong Li · 2021
With the continuous popularity of the Internet, network security has received more and more attention. Compared with intrusions from outside the network, abnormal operations of internal users often pose a greater threat to system security. Audit log analysis can discover abnormal behaviors or illegal operations of internal users through technologies such as data mining and pattern comparison, thereby adjusting security policies to ensure system security. Based on the FP-growth algorithm, this paper proposes an improved algorithm NEFP (New Efficient FP-growth) that does not generate conditional frequent pattern tree, and proposes an implementation plan for audit log analysis based on NEFP algorithm. Experimental results show that NEFP algorithm can perform log audit analysis more efficiently.