Revisiting Higher-Order DPA Attacks: Multivariate Mutual Information Analysis.
Benedikt Gierlichs, Lejla Batina, Bart Preneel, Ingrid M.R. Verbauwhede · 2009
Abstract. Security devices are vulnerable to side-channel attacks that perform statistical analysis on data leaked from cryptographic computa-tions. Higher-order (HO) attacks are a powerful approach to break pro-tected implementations. They inherently demand multivariate statistics because multiple aspects of signals have to be analyzed jointly. How-ever, most works on HO attacks follow the approach to first apply a pre-processing function to map the multivariate problem to a univariate problem and then to apply established 1st order techniques. We propose a novel and different approach to HO attacks, Multivariate Mutual Infor-mation Analysis (MMIA), that allows to directly evaluate joint statistics without pre-processing. While this approach can benefit from a good power model, it also works without an assumption. We present the first experimental results for 2nd and 3rd order MMIA as well as state-of-the-art HO attacks based on real measurements. A thorough empirical evaluation confirms the advantage of the new approach: 3rd order MMIA attacks require about 800 measurements to achieve 100 % success while state-of-the-art HODPA requires 1000 measurements to achieve about 40 % success. As a consequence, the security provided by the masking countermeasure needs to be reconsidered as 3rd and possibly higher or-der attacks become more practical. 1