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Privacy-Preserving Robustness-Guided Testing

Charles Koll, Houssam Abbas, Mike Rosulek · 2026 · IEEE Embedded Systems Letters

DOI: 10.1109/les.2026.3728778 · cited by 0 works (OpenAlex) · open-access PDF

French

Dans des industries telles que les semi-conducteurs et l'aéronautique, il est courant pour la société de conception de souscrire une partie du processus de test à une société de Testing-as-a-Service (TaaS). Dans une telle configuration, les deux parties veulent garder leur propriété intellectuelle privée (c'est-à-dire inconnue de l'autre partie): à savoir la conception et ses traces de sortie pour le concepteur, et les spécifications de précision détaillées pour le testeur. Nous démontrons un moyen pratique pour mener à bien TaaS privé en utilisant un protocole de calcul multi-parties cryptographiquement sécurisé. Nous le faisons pour la configuration commune où la spécification est dans Signal Temporal Logic, et le test est effectué en

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Abstract

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.

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Topics: Correctness, Computer science, Overhead (engineering), Process (computing), Property (philosophy), Computation

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