Memory errors have long been a critical security issue primarily for C/C++ programming languages and are still considered one of the top three most dangerous software errors according to the MITRE ranking. In this paper the authors focus on their exploitation via control-flow hijacking and data-only attacks (stack, and partially heap (G. Novarck & E. Berger, 2010)) by proposing a synergistic security methodology, which can accurately detect and thwart them. Their methodology is based on the Dynamic Information Flow Tracking (DIFT) technique and improves its data-only attack detection by utilizing features from the Reverse Stack Execution (RSE) security technique. Thus, the authors can significantly lower the resource consumption of the latter methodology, while increasing the former's accuracy. Their proof-of-concept compiler implementation verifies their assumptions and is able to protect vulnerable C programs against various real-world attack scenarios.
A Game-Theoretic Approach for Dynamic Information Flow Tracking to Detect Multistage Advanced Persistent Threats
