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.