Semi-automatic ladderisation: improving code security through rewriting and dependent types - Inria - Institut national de recherche en sciences et technologies du numérique
Conference Papers Year : 2022

Semi-automatic ladderisation: improving code security through rewriting and dependent types

Abstract

Cyber attacks become more and more prevalent every day. One type of cyber attack is known as a side channel attack, where attackers exploit information leakage from the physical execution of a program, e.g. timing or power leakage, to uncover secret information, such as encryption keys or other sensitive data. There have been various attempts at addressing the problem of preventing side-channel attacks, often relying on various measures to decrease the discernibility of several code variants or code paths. Most techniques require a high-degree of expertise by the developer, who often employs ad hoc, hand-crafted code-patching in an attempt to make it more secure. In this paper, we take a different approach: building on the idea of ladderisation, inspired by Montgomery Ladders. We present a semi-automatic tool-supported technique, aimed at the non-specialised developer, which refactors (a class of) C programs into functionally (and even algorithmically) equivalent counterparts with improved security properties. Our approach provides refactorings that transform the source code into its ladderised equivalent, driven by an underlying verified rewrite system, based on dependent types. Our rewrite system automatically finds rewritings of selected C expressions, facilitating the production of their equivalent ladderised counterparts for a subset of C. We demonstrate our approach on a number of representative examples from the cryptographic domain, showing increased security.
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Dates and versions

hal-03805561 , version 1 (07-10-2022)

Identifiers

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Christopher Brown, Adam Barwell, Yoann Marquer, Olivier Zendra, Tania Richmond, et al.. Semi-automatic ladderisation: improving code security through rewriting and dependent types. PEPM 2022 - ACM SIGPLAN International Workshop on Partial Evaluation and Program Manipulation, Jan 2022, Philadelphia PA, United States. pp.14-27, ⟨10.1145/3498886.3502202⟩. ⟨hal-03805561⟩
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