Abstract
System log files contain valuable evidence pertaining to computer attacks. However, the log files are often massive, and much of the information they contain is not relevant to the investigation. Furthermore, the files almost always have a flat structure, which limits the ability to query them. Thus, digital forensic investigators find it extremely difficult and time consuming to extract and analyze evidence of attacks from log files. This paper describes an automated attack-tree-based approach for filtering irrelevant information from system log files and conducting systematic investigations of computer attacks.
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