A Systematic Evaluation of Wavelet-Based Attack Framework on Random Delay Countermeasures

Abstract

Random delay countermeasure is a commonly used defense against side-channel attacks, which brings certain interference and disturbance to those calculation sequences in the time domain. Data alignment and frequency attack are considered as typical techniques to counteract the random delay countermeasure. However, these attacks have limitations from the perspectives of both efficiency and performance. In comparison, facing those delays, wavelet analysis is considered as a more efficient technique due to its detailed and comprehensive interpretation of a signal. This paper applies different wavelet techniques to three attack components: noise reduction, trace alignment and key extraction. For the first time, the unified wavelet-based attack framework against random delays is proposed where wavelet analysis is fully applied in the entire attack life cycle. In particular, a novel method of trace alignment at the wavelet level is proposed in this framework, which is based on wavelet pattern detection to synchronize the misaligned power traces. Most importantly, the overall wavelet-based attack framework is systematically evaluated over three random delay strategies, after the respective contribution of each component is investigated through a series of comparative experiments. Experimental results show that the performance of the wavelet-based attack framework is significantly improved compared to standard attack procedures and frequency ones, which can be regarded as a unified and effective solution to conquer random delay countermeasures.