Yubo Zhao
School of Computer Science, Shanghai Jiao Tong University, Shanghai, China

Shipei Qu
School of Computer Science, Shanghai Jiao Tong University, Shanghai, China

Yuxuan Wang
School of Computer Science, Shanghai Jiao Tong University, Shanghai, China

Jintong Yu
School of Computer Science, Shanghai Jiao Tong University, Shanghai, China

Juncheng Ji
School of Computer Science, Shanghai Jiao Tong University, Shanghai, China

Zhiliang An
School of Computer Science, Shanghai Jiao Tong University, Shanghai, China

Chi Zhang
School of Computer Science, Shanghai Jiao Tong University, Shanghai, China

Zhedong Wang
School of Computer Science, Shanghai Jiao Tong University, Shanghai, China

Dawu Gu
School of Computer Science, Shanghai Jiao Tong University, Shanghai, China

Keywords: Side-Channel Analysis, Cryptographic Operation Localization, Time-Frequency Analysis, Time-Series Analysis

Abstract

Accurate localization of Cryptographic Operations (COs) in long, noisy side-channel traces is important for effective Side-Channel Analysis (SCA). Existing techniques either search for repeated temporally contiguous patterns directly in raw traces or rely on profiling devices to derive templates or learned models.In this paper, we present SpectroLoc, a profiling-free framework for CO localization based on a spectral activity projection derived from the trace spectrogram. In this representation, narrowband noise components tend to form a relatively stable baseline, while CO-related activity remains distinguishable over time.Building on this representation, SpectroLoc supports three common localization tasks: (i) localization of single recurring COs through intra-trace self-templating; (ii) unsupervised coarse-grained segmentation of complex COs via change-point detection; and (iii) distinction of interleaved COs via motif discovery.Experiments on multiple public datasets, including long ECDSA traces and AES-128 implementations protected by random-delay countermeasures, show that SpectroLoc achieves competitive hit rates and lower runtime than the prior non-profiling baseline on the evaluated tasks. These results suggest that SpectroLoc provides a practical CO localization tool for side-channel analysis.