DECIFR: Domain-Aware Exfiltration of Circuit Information from Federated Gradient Reconstruction

Computer Science > Cryptography and Security [Submitted on 21 Apr 2026] DECIFR: Domain-Aware Exfiltration of Circuit Information from Federated Gradient Reconstruction Gijung Lee, Wavid Bowman, Olivia P. Dizon-Paradis, Reiner N. Dizon-Paradis, Ronald Wilson, Damon L. Woodard, Domenic Forte Federated Learning (FL) is a promising approach for multiparty collaboration as a privacy-preserving technique in hardware assurance, but its security against adversaries with domain-specific knowledge is underexplored. This paper demonstrates a critical vulnerability where available standard cell library layouts (SCLL) can be exploited to compromise the privacy of sensitive integrated circuit (IC) training data. We introduce DECIFR, a novel two-stage Membership Inference Attack (MIA) that requires no auxiliary dataset. The attack employs a guided Gradient Inversion Attack (GIA) to reconstruct a client's training images from intercepted model updates. Our findings reveal that the fidelity of these reconstructions directly correlates with membership status, allowing an adversary to reliably distinguish members from non-members based on image quality. This work exposes a practical threat that overcomes the limitations of conventional attacks and underscores that standard FL protocols are insufficient for securing domains with extensive knowledge. We conclude that robust defenses are essential for the secure application of FL in hardware assurance. Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2604.19915 [cs.CR]   (or arXiv:2604.19915v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2604.19915 Focus to learn more Submission history From: Gijung Lee [view email] [v1] Tue, 21 Apr 2026 18:48:58 UTC (4,360 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-04 Change to browse by: cs 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?)