Multi-Partner Project

Securing Future Edge-AI Processors in Practice (CONVOLVE)

Conference Paper (2025)
Author(s)

Sven Argo (Ruhr-Universität Bochum)

Henk Corporaal (Eindhoven University of Technology)

Alejandro Garza (Nxp Semiconductors)

Marc Geilen (Eindhoven University of Technology)

Manil Dev Gomony (Eindhoven University of Technology)

Tim Güneysu (Ruhr-Universität Bochum, Deutsches Forschungszentrum für Künstliche Intelligenz)

Fouwad Mir (TU Delft - Electrical Engineering, Mathematics and Computer Science, CognitiveIC)

Mottaqiallah Taouil (CognitiveIC, TU Delft - Electrical Engineering, Mathematics and Computer Science)

Said Hamdioui (CognitiveIC, TU Delft - Electrical Engineering, Mathematics and Computer Science)

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Research Group
Computer Engineering
DOI related publication
https://doi.org/10.23919/DATE64628.2025.10993210 Final published version
More Info
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Publication Year
2025
Language
English
Research Group
Computer Engineering
Publisher
IEEE
ISBN (electronic)
9783982674100
Event
2025 Design, Automation and Test in Europe Conference, DATE 2025 (2025-03-31 - 2025-04-02), Lyon, France
Page Views
49
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Abstract

Artificial Intelligence (AI) has had a profound impact on our contemporary society, and it is indisputable that it will continue to play a significant role in the future. To further enhance AI experience and performance, a transition from large-scale server applications towards AI-powered edge devices is inevitable. In fact, current projections indicate that the market for Smart Edge Processors (SEPs) will grow beyond 70 Billion USD by 2026 [1]. Such a shift comes with major challenges, as these devices have limited computing and energy resources yet need to be highly performant. Additionally, security mechanisms need to be implemented to protect against diverse attack vectors as attackers now have physical access to the device. Besides cryptographic keys, Intellectual Property (IP), including neural network weights, may also be potential targets. The CONVOLVE [2] project (currently in its intermediate stage) follows a holistic approach to address these challenges and establish the EU in a leading position in embedded, ultra-low-power and secure processors for edge computing. It encompasses novel hardware technologies, end-to-end integrated workflows, and a security-by-design approach. This paper highlights the security aspects of future edge-AI processors by illustrating challenges encountered in CONVOLVE, the solutions we pursue including some early results, and directions for future research.

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