Building forensics in: supporting the investigation of digital criminal activities (invited talk)

Abstract

Logging mechanisms that capture detailed traces of user activity, including creating, reading, updating, and deleting (CRUD) data, facilitate meaningful forensic analysis following a security or privacy breach. However, software requirements often inadequately and inconsistently state 'what' user actions should be logged, thus hindering meaningful forensic analysis. In this talk, we will explore a variety of techniques for building a software system that supports forensic analysis. We will discuss systematic heuristics-driven and patterns-driven processes for identifying log events that must be logged based on user actions and potential accidental and malicious use, as described in natural language software artifacts. We then discuss systematic process for creating a black-box test suite for verifying the identified log events are logged. Using the results of executing the black-box test suite, we propose and evaluate a security metric for measuring the forensic-ability of user activity logs.