Attacking AI Accelerators by Leveraging Arithmetic Properties of Addition

Computer Science > Cryptography and Security [Submitted on 28 Mar 2026] Attacking AI Accelerators by Leveraging Arithmetic Properties of Addition Masoud Heidary, Biresh Kumar Joardar The dependability of AI models relies largely on the reliability of the underlying computation hardware. Hardware aging attacks can compromise the computing substrate and disrupt AI models over the long run. In this work, we present a new hardware aging attack that exploits commutative properties of addition to disrupt the multiply-and-add operation that forms the backbone of almost all AI models. By permuting the inputs of an adder, the attack preserves functional correctness while inducing unbalanced stress among transistors, accelerating delay degradation in the circuit. Unlike prior approaches that rely on input manipulation, additional trojan circuitry, etc., the proposed method incurs virtually no area or software overhead. Experimental results with two types of multipliers, different bit widths, a mix of AI models and datasets demonstrates that the proposed attack degrades inference accuracy by up to 64% in 4 years, posing a significant threat to AI accelerators. The attack can also be extended to arithmetic units of general-purpose processors. Comments: 10 pages, 11 figures Subjects: Cryptography and Security (cs.CR); Hardware Architecture (cs.AR) Cite as: arXiv:2603.27439 [cs.CR]   (or arXiv:2603.27439v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2603.27439 Focus to learn more Submission history From: Biresh Kumar Joardar [view email] [v1] Sat, 28 Mar 2026 23:03:27 UTC (1,323 KB) Access Paper: view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-03 Change to browse by: cs cs.AR References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)