A Cascade Approach for APT Campaign Attribution in System Event Logs: Technique Hunting and Subgraph Matching

As Advanced Persistent Threats (APTs) grow increasingly sophisticated, the demand for effective detection methods has intensified. This study addresses the challenge of identifying APT campaign attacks through system event logs. A cascading approach, name SFM, combines Technique hunting and APT campaign attribution. The approach assumes that real-world system event logs contain a vast majority of normal events interspersed with few suspiciously malicious ones and that the logs are annotated with Techniques of MITRE ATT&CK framework for attack pattern recognition. After identifying Techniques from the log, we attribute APT campaign attacks by aligning detected Techniques with known attack sequences to determine the most likely APT campaign. Evaluations on five synthetic real-world APT campaigns indicate that the proposed approach demonstrates reliable performance.