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Privacy-Preserving Robustness-Guided Testing
Charles Koll, Houssam Abbas, Mike Rosulek

Privacy-Preserving Robustness-Guided Testing

Science & Mathematics Published 2026 Verification Pending

Overview & Synopsis

In industries like semi-conductors and aerospace, it is common for the design company to contract out part of the testing process to a Testing-as-a-Service (TaaS) company. In such a setup, both parties want to keep their intellectual property private (i.e. unknown to the other party): namely the design and its output traces for the designer, and the detailed correctness specifications for the tester. We demonstrate a practical way for conducting provably private TaaS using a cryptographically secure multi-party computation protocol. We do so for the common setup where the specification is in Signal Temporal Logic, and testing is done using robustness-guided falsification. Our implementation carefully separates the steps of falsification, and manages to be $\textit{maximally secure}$, in the sense that the parties learn the absolutely minimum necessary for falsification. For up to a 100-dimensional input search space, the generation of one test takes less than 80 msec, and the overhead of the privacy-preserving protocol is less than 6x. These numbers mean that privacy-preserving TaaS is practical, thus enabling TaaS in security-sensitive industries.

Indexed from repository: arXiv (arxiv.org)
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Document Information

Document Title Privacy-Preserving Robustness-Guided Testing
Author / Organization Charles Koll, Houssam Abbas, Mike Rosulek
Subject & Discipline cs.CR
Categories Science & Mathematics
Publication Year 2026
License / Rights arXiv Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website arXiv (arxiv.org)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-271414
Original Source Link Visit Source Page on arxiv.org »