CRESTS: Chronology-based Reconstruction for Side-Channel Trace Segmentation for XTS-AES on Complex Targets - Krüger, Paul; Wildermann, Stefan; Teich, Jürgen (EUROSEC '24: Proceedings of the 17th European Workshop on System Security, 2024)
Physical Side-Channel Analysis (SCA) is often restricted to less complex devices, such as microcontrollers, as more feature-rich targets, like microprocessor systems, contain possibly multiple sources of systemic noise that influence side-channels and their waveforms non-deterministically in the view of an observer. Thus, locating these waveforms using established waveform matching techniques and subsequent data association becomes impossible. This impedes the application of SCA techniques relying on the relationship of operation waveforms and their processed data. In order to address this issue, this paper presents the CRESTS algorithm, that is capable of locating instances of target operations in larger side-channel traces affected by systemic noise. This enables to extract the waveforms of the relevant operations from the trace and, by maintaining their overall sequence of occurrence, associate them with their corresponding data to then apply established SCA techniques. The effectiveness of our approach is evaluated by applying CRESTS on the widespread XTS-AES algorithm running on a Beaglebone Black System-on-Chip (SoC) target platform.<br
Keywords: Side-Channel Analysis; Feature Selection; Heuristic