Multi-Partner Project: Securing Future Edge-AI Processors in Practice (CONVOLVE)

Sven Argo; Henk Corporaal; Alejandro Garza; Marc Geilen; Manil Dev Gomony; Tim Güneysu; Adrian Marotzke; Fouwad Mir; Christian Larmann; Jan Richter-Brockmann; Jeffrey Smith; Mottaqiallah Taouil; Said Hamdioui

Paper 2025/1431

Multi-Partner Project: Securing Future Edge-AI Processors in Practice (CONVOLVE)

Sven Argo

, Ruhr University Bochum

Henk Corporaal

, Eindhoven University of Technology

Alejandro Garza

, NXP (Germany)

Marc Geilen

, Eindhoven University of Technology

Manil Dev Gomony

, Eindhoven University of Technology

Tim Güneysu

, Ruhr University Bochum, German Research Centre for Artificial Intelligence

Adrian Marotzke

, NXP (Germany), Hamburg University of Technology

Fouwad Mir

, Delft University of Technology, CognitiveIC

Christian Larmann, Delft University of Technology, CognitiveIC

Jan Richter-Brockmann

, Ruhr University Bochum

Jeffrey Smith, Eindhoven University of Technology

Mottaqiallah Taouil

, Delft University of Technology, CognitiveIC

Said Hamdioui

, Delft University of Technology, CognitiveIC

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.

Metadata

Available format(s): PDF
Category: Applications
Publication info: Published elsewhere. Minor revision. 2025 Design, Automation & Test in Europe Conference (DATE)
DOI: 10.23919/DATE64628.2025.10993210
Keywords: PQC TEE composability real-time CIM
Contact author(s): sven argo @ rub de
h corporaal @ tue nl
alejandro garza @ nxp com
m c w geilen @ tue nl
m gomony @ tue nl
tim gueneysu @ rub de
adrian marotzke @ nxp com
F J Mir @ tudelft nl
jan richter-brockmann @ rub de
M Taouil @ tudelft nl
S Hamdioui @ tudelft nl
History: 2025-08-07: approved; 2025-08-06: received; See all versions
Short URL: https://ia.cr/2025/1431
License: CC BY

BibTeX

@misc{cryptoeprint:2025/1431,
      author = {Sven Argo and Henk Corporaal and Alejandro Garza and Marc Geilen and Manil Dev Gomony and Tim Güneysu and Adrian Marotzke and Fouwad Mir and Christian Larmann and Jan Richter-Brockmann and Jeffrey Smith and Mottaqiallah Taouil and Said Hamdioui},
      title = {Multi-Partner Project: Securing Future Edge-{AI} Processors in Practice ({CONVOLVE})},
      howpublished = {Cryptology {ePrint} Archive, Paper 2025/1431},
      year = {2025},
      doi = {10.23919/DATE64628.2025.10993210},
      url = {https://eprint.iacr.org/2025/1431}
}