PBDG: a malicious code detection method based on precise behaviour dependency graph
Chenghua Tang, Mengmeng Yang, Qingze Gao, Baohua Qiang · International Journal of Information and Computer Security · 2024
Using behaviour association or dependency to detect malicious code can improve the recognition rate of malicious code. A malicious code detection method based on precise behaviour dependency graph (PBDG) is proposed. We create a stain file index by filtering the stain source blacklist, which not only saves storage space, but also quickly locates instructions. An active variable path verification algorithm is proposed to verify and purify the Source → Sink path. The PBDG and its matching algorithm are constructed to identify the malicious code family of the source program. The experimental results on six data sets show the effectiveness of this method. The introduction of active variable paths reduces the number of paths that need to be traversed by 91.2% at most. In terms of the detection effect of malicious code, especially for web applications, it has a good detection accuracy and a low false positive rate.