CAMFAS: A Compiler Approach to Mitigate Fault Attacks via Enhanced SIMDization
Zhi Chen, Junjie Shen, Alex Nicolau, Alex V. Veidenbaum, Nahid Farhady Ghalaty, Rosario Cammarota · 2017
The trend of supporting wide vector units in general purpose microprocessors suggests opportunities for developing a new and elegant compilation approach to mitigate the impact of faults to cryptographic implementations, which we present in this work. We propose a compilation flow, CAMFAS, to automatically and selectively introduce vectorization in a cryptographic library - to translate a vanilla library into a library with vectorized code that is resistant to glitches. Unlike in traditional vectorization, the proposed compilation flow uses the extent of the vectors to introduce spatial redundancy in the intermediate computations. By doing so, without significantly increasing code size and execution time, the compilation flow provides sufficient redundancy in the data to detect errors in the intermediate values of the computation. Experimental results show that the proposed approach only generates an average of 26% more dynamic instructions over a series of asymmetric cryptographic algorithms in the Libgcrypt library.