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UID:dac_DAC 2026_sess315_RESEARCH2369@linklings.com
SUMMARY:ReConnaissance: Correctly Tracking Multiple Secrets using Reveal/C
 onceal Paradigms
DESCRIPTION:Amund Bergland Kvalsvik and Magnus Sjalander (Norwegian Univer
 sity of Science and Technology)\n\nSecure speculation schemes are critical
  for defeating speculative side-channel attacks, but often incur notable p
 erformance penalties, encouraging research into optimization strategies. O
 ne such optimization strategy, ReCon, improves performance by exploiting p
 revious non-speculative data leakage to remove protections for already lea
 ked data. However, we find that ReCon can leak secrets when an instruction
  depends on multiple sources of potentially secret data. We show how inter
 actions between Speculative Taint Tracking (STT) and ReCon results in ReCo
 n undermining STT's security guarantees. We address this oversight through
  a low-impact multi-source tracking mechanism that we call ReConnaissance.
  Together with a detailed microarchitecture, we show that, on average, ReC
 onnaissance only lowers the overhead-reduction of ReCon from 23.5% to 18.3
 % on SPEC2017.\n\nTopics: Quantum\n\nTrack: DES6. Quantum Computing, Syste
 ms\n\nSession Chairs: Hokeun Kim (Arizona State University); BaekGyu Kim (
 Daegu Gyeongbuk Institute of Science and Technology); Xiang Chen (Peking U
 niversity); Sangyeob Kim (Yonsei University); Robert M. Radway (University
  of Pennsylvania); Prashanth Mohan (University of Pittsburgh); Xiaoxuan Ya
 ng (University of Virginia, Stanford University); Ramtin Zand (University 
 of South Carolina); Hadi Kamali (University of Central Florida); Jiafeng X
 ie (Villanova University); Prabuddha Chakraborty (University of Maine); Ju
 nichiro Kadomoto (University of Tokyo); and Yosuke Ueno (RIKEN)\n\n
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