An Enhanced Dataflow Analysis to Automatically Tailor Side Channel Attack Countermeasures to Software Block Ciphers

Protecting software implementations of block ciphers from side channel attacks is a significant concern to realize secure embedded computation platforms. The relevance of the issue calls for the automation of the side channel vulnerability assessment of a block cipher implementation, and the automated application of provably secure defenses. The most recent methodology in the field is an application of a specialized data-flow analysis, performed by means of the LLVM compiler framework, detecting in the AES cipher the portions of the code amenable to key extraction via side channel analysis. The contribution of this work is an enhancement to the existing data-flow analysis which extending it to tackle any block cipher implemented in software. In particular, the extended strategy takes fully into account the data dependencies present in the key schedule of a block cipher, regardless of its complexity, to obtain consistently sound results. This paper details the analysis strategy and presents new results on the tailored application of power and electro-magnetic emission analysis countermeasures, evaluating the performances on both the ARM Cortex-M and the MIPS ISA. The experimental evaluation reports a case study on two block ciphers: the first designed to achieve a high security margin at a non-negligible computational cost, and a lightweight one. The results show that, when side-channel-protected implementations are considered, the high-security block cipher is indeed more efficient than the lightweight one

Automated instantiation of side-channel attacks countermeasures for software cipher implementations

Side Channel Attacks (SCA) have proven to be a practical threat to the security of embedded systems, exploiting the information leakage coming from unintended channels concerning an implementation of a cryptographic primitive. Given the large variety of embedded platforms, and the ubiquity of the need for secure cryptographic implementations, a systematic and automated approach to deploy SCA countermeasures at design time is strongly needed. In this paper, we provide an overview of recent compiler-based techniques to protect software implementations against SCA, making them amenable to automated application in the development of secure-by-design systems

Encasing Block Ciphers to Foil Key Recovery Attempts via Side Channel

Providing efficient protection against energy consumption based side channel attacks (SCAs) for block ciphers is a relevant topic for the research community, as current overheads are in the 100× range. Unprofiled SCAs exploit information leakage from the outmost rounds of a cipher; we propose a solution encasing it between keyed transformations amenable to an efficient SCA protection. Our solution can be employed as a drop in replacement for an unprotected implementation, or be retrofit to an existing one, while retaining communication capabilities with legacy insecure endpoints. Experiments on a Cortex-M4 μC, show performance improvements in the range of 60×, compared with available solutions

Compiler-based Side Channel Vulnerability Analysis and Optimized Countermeasures Application

Modern embedded systems manage sensitive data increasingly often through cryptographic primitives. In this context, side-channel attacks, such as power analysis, represent a concrete threat, regardless of the mathematical strength of a cipher. Evaluating the resistance against power analysis of cryptographic implementations and preventing it, are tasks usually ascribed to the expertise of the system designer. This paper introduces a new security-oriented data-flow analysis assessing the vulnerability level of a cipher with bit-level accuracy. A general and extensible compiler-based tool was implemented to assess the instruction resistance against power-based side-channels. The tool automatically instantiates the essential masking countermeasures, yielding a ×2.5 performance speedup w.r.t. protecting the entire code