Dev Mehta, Seyedmohammad Nouraniboosjin, Maryam S. Safa, Shahin Tajik, and Fatemeh Ganji, Worcester Polytechnic Institute
Despite decades of research in electromagnetic (EM) side-channel analysis (SCA), practical attacks still require manual effort and domain expertise to identify informative probe locations on target devices. Existing approaches rely heavily on exhaustive grid scanning or handcrafted alignment, limiting attack scalability and realism. In this work, we present the first automated and adaptive EM SCA framework that uses particle swarm optimization (PSO) to navigate the probe. Particles are guided by mutual information (MI) leakage maps, enabling efficient recovery of secret-dependent emissions. We introduce a novel application of the Nyström approximation to accelerate MI estimation across EM trace windows, allowing real-time swarm guidance without full kernel computations. Unlike prior work, our method requires no leakage templates, manual tuning, or alignment assistance—enabling automated attacks with minimal assumptions. We validate our framework on both microcontroller and FPGA platforms running AES-128. PSO-guided scanning identifies high-leakage points faster than grid search and reduces the number of traces required for successful CPA-based key recovery by up to a factor of 16, i.e., saving tens of thousands of traces.
