Binary data analysis for source code leakage assessment

Abstract

Side Channel Analysis (SCA) is known to be a serious threat for cryptographic algorithms since twenty years. Recently, the explosion of the Internet of Things (IoT) has increased the number of devices that can be targeted by these attacks, making this threat more relevant than ever. Furthermore, the evaluations of cryptographic algorithms regarding SCA are usually performed at the very end of a product design cycle, impacting considerably the time-to-market in case of security flaws. Hence, early simulations of embedded software and methodologies have been developed to assess vulnerabilities with respect to SCA for specific hardware architectures. Aiming to provide an agnostic evaluation method, we propose in this paper a new methodology of data collection and analysis to reveal leakage of sensitive information from any software implementation. As an illustration our solution is used interestingly to break a White Box Cryptography (WBC) implementation, challenging existing simulation-based attacks.