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Hardware Security for Silicon Photonic-Based AI Accelerators

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A technical paper titled “Integrated Photonic AI Accelerators under Hardware Security Attacks: Impacts and Countermeasures” was published by researchers at Ecole Polytechnique de Montreal and Colorado State University.

Abstract:

“Integrated photonics based on silicon photonics platform is driving several application domains, from enabling ultra-fast chip-scale communication in high-performance computing systems to energy-efficient optical computation in artificial intelligence (AI) hardware accelerators. Integrating silicon photonics into a system necessitates the adoption of interfaces between the photonic and the electronic subsystems, which are required for buffering data and optical-to-electrical and electrical-to-optical conversions. Consequently, this can lead to new and inevitable security breaches that cannot be fully addressed using hardware security solutions proposed for purely electronic systems. This paper explores different types of attacks profiting from such breaches in integrated photonic neural network accelerators. We show the impact of these attacks on the system performance (i.e., power and phase distributions, which impact accuracy) and possible solutions to counter such attacks.”

Find the technical paper here. Published September 2023 (preprint).

de Magalhães, Felipe Gohring, Mahdi Nikdast, and Gabriela Nicolescu. “Integrated Photonic AI Accelerators under Hardware Security Attacks: Impacts and Countermeasures.” arXiv preprint arXiv:2309.02543 (2023).

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