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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20260402T024533Z
LOCATION:3003\, Level 3
DTSTART;TZID=America/Los_Angeles:20250623T111500
DTEND;TZID=America/Los_Angeles:20250623T113000
UID:dac_DAC 2025_sess152_RESEARCH663@linklings.com
SUMMARY:Cross-Attention for AES Mode Variation in Side-Channel Analysis
DESCRIPTION:Fanliang Hu (Nanjing University of Information Science and Tec
 hnology), Jian Shen and Haoyu Ma (Zhejiang Sci-Tech University), and Qingm
 ing Jonathan Wu (University of Windsor)\n\nPortability poses a significant
  challenge for Deep Learning (DL)-based profiling Side-Channel Analysis (S
 CA) on AES encryption, as attackers cannot always ensure that training and
  target samples use the same encryption mode. To address this, we propose 
 an Unsupervised Domain Adaptation (UDA) DL-SCA framework for achieving eff
 ective and robust cross-encryption-mode attacks. By incorporating cross-at
 tention and UDA techniques, our framework aligns high-dimensional input sa
 mples, reducing interference from encryption mode mismatches. Evaluation a
 cross five distinct AES modes demonstrates that our method achieves robust
  SCA performance without requiring prior knowledge or multiple labeled dat
 asets for analysis.\n\nTopics: Security\n\nTracks: SEC3: Hardware Security
 : Attack & Defense\n\nSession Chairs: Michael Zuzak (Rochester Institute o
 f Technology) and Prabuddha Chakraborty (University of Maine)\n\n
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