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UID:dac_DAC 2026_sess317_RESEARCH1732@linklings.com
SUMMARY:Drop-In Masked Modular Reduction for ML-DSA: Cutting Side-Channel 
 Cost in the Root-of-Trust
DESCRIPTION:Merve Karabulut and Reza Azarderakhsh (Florida Atlantic Univer
 sity)\n\nMasking is an effective defense against side-channel attacks, yet
  it remains costly under hardware constraints. The Caliptra Root-of-Trust 
 is a representative case, where its masked ML-DSA implementation incurs ab
 out 6× area overhead. We propose a novel first-order masking solution that
  optimizes Caliptra, achieving significant improvements in area–delay effi
 ciency. Compared to Caliptra's ML-DSA reduction, our design achieves a 12.
 1× speedup, reducing LUTs by 86.7% and FFs by 94.5%, while improving area–
 delay efficiency by 91×. The optimized architecture increases signing thro
 ughput by 1.32×. TVLA, with over 1,000,000 traces, shows no first-order le
 akage, satisfies Caliptra's security requirements, and significantly impro
 ves implementation efficiency.\n\nTrack: EDA7-II. Physical Design and Veri
 fication, Design\n\nSession Chairs: Christian Pilato (Politecnico di Milan
 o); Mohsen Imani (University of California, Irvine); Flavio Ponzina (San D
 iego State University); Amin Farshidi (Cadence Design Systems, Inc.); Yong
 gan Fu (Georgia Institute of Technology, NVIDIA); Dimitrios Tsaras (Huawei
 , Hong Kong University of Science and Technology (HKUST)); Anh Nguyen (Fuj
 itsu Limited); Ruiyang Qin (Villanova University); Jiliang Zhang (Hunan Un
 iversity); Meng Li (Peking University); and Rassul Bairamkulov (Advanced M
 icro Devices (AMD))\n\n
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