Detecting Ransomware Attacks by Analyzing Replicated Block Snapshots Using Neural Networks

초록

Cloudantivirus solutions address limitations of host-based malware detection such as extensive resource consumption. However, they remain vulnerable to sophisticated polymorphic and privileged malware. Also, existing solutions are not suitable to defend against destructive ransomware attacks. We propose an enhancement to existing cloud antivirus solutions that enables deep learning-based block snapshot analysis to detect evasive and privileged ransomware in virtualized environment without requiring any hardware support. Preliminary results validate the proposed approach.

키워드