Abstract. We introduce new methods for detecting control-flow side channel attacks, transforming C source code to eliminate such attacks, and checking that the transformed code is free of control-flow side channels. We model control-flow side channels with a program counter transcript, in which the value of the program counter at each step is leaked to an adversary. The program counter transcript model captures a class of side channel attacks that includes timing attacks and error disclosure attacks. Further, we propose a generic source-to-source transformation that produces programs provably secure against control-flow side channel attacks. We implemented this transform for C together with a static checker that conservatively checks x86 assembly for violations of program counter security; our checker allows us to compile with optimizations while retaining assurance the resulting code is secure. We then measured our technique’s effect on the performance of binary modular exponentiation and real-world implementations in C of RC5 and IDEA: we found it has a performance overhead of at most 5 × and a stack space overhead of at most 2×. Our approach to side channel security is practical, generally applicable, and provably secure against an interesting class of side channel attacks. 1

Abstract: Intrusion Detection Systems (IDS) are responsible for monitoring and analyzing host or network activity to detect intrusions in order to protect information from unauthorized access or manipulation. There are two main approaches for intrusion detection: signature-based and anomaly-based. Signature-based detection employs pattern matching to match attack signatures with observed data making it ideal for detecting known attacks. However, it cannot detect unknown attacks for which there is no signature available. Anomaly-based detection uses machine-learning techniques to create a profile of normal system behavior and uses this profile to detect deviations from the normal behavior. Although this technique is effective in detecting unknown attacks, it has a drawback of a high false alarm rate. In this paper, we describe our anomaly-based IDS designed for detecting malicious use of cryptographic and application-level protocols. Our system has several unique characteristics and benefits, such as the ability to monitor cryptographic protocols and application-level protocols embedded in encrypted sessions, a very lightweight monitoring process, and the ability to react to protocol misuse by modifying protocol response directly.

In this paper, we argue that heterogeneity should be an important principle in design and use of cryptographic protocols. We use automated formal analysis tools to randomly generate security protocols as a method of introducing heterogeneity. We present the results of simulations for the case of two party authentication protocols and argue that choosing protocols randomly out of sets numbering in the hundreds of millions is practical and achievable with an acceptable overhead. To realize the simulation, we implemented a highly efficient protocol verifier, achieving approximately two orders of magnitude improvement in performance compared to previous work.