You Are What You Do: Hunting Stealthy Malware via Data Provenance Analysis
Qi Wang, Wajih Ul Hassan, Ding Li, Kangkook Jee, Xiao Yu, Kexuan Zou, Junghwan Rhee, Zhengzhang Chen, Wei Cheng, Carl A. Gunter, Haifeng Chen
Abstract
To subvert recent advances in perimeter and host security, the attacker community has developed and employed various attack vectors to make a malware much stealthier than before to penetrate the target system and prolong its presence. Such advanced malware or "stealthy malware" makes use of various techniques to impersonate or abuse benign applications and legitimate system tools to minimize its footprints in the target system. It is thus difficult for traditional detection tools, such as malware scanners, to detect it, as the malware normally does not expose its malicious payload in a file and hides its malicious behaviors among the benign behaviors of the processes.