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A Survey and Perspective on Artificial Intelligence for Security-Aware Electronic Design Automation

Machine Learning 2022-04-22 v2 Artificial Intelligence Cryptography and Security

Abstract

Artificial intelligence (AI) and machine learning (ML) techniques have been increasingly used in several fields to improve performance and the level of automation. In recent years, this use has exponentially increased due to the advancement of high-performance computing and the ever increasing size of data. One of such fields is that of hardware design; specifically the design of digital and analog integrated circuits~(ICs), where AI/ ML techniques have been extensively used to address ever-increasing design complexity, aggressive time-to-market, and the growing number of ubiquitous interconnected devices (IoT). However, the security concerns and issues related to IC design have been highly overlooked. In this paper, we summarize the state-of-the-art in AL/ML for circuit design/optimization, security and engineering challenges, research in security-aware CAD/EDA, and future research directions and needs for using AI/ML for security-aware circuit design.

Keywords

Cite

@article{arxiv.2204.09579,
  title  = {A Survey and Perspective on Artificial Intelligence for Security-Aware Electronic Design Automation},
  author = {David Selasi Koblah and Rabin Yu Acharya and Daniel Capecci and Olivia P. Dizon-Paradis and Shahin Tajik and Fatemeh Ganji and Damon L. Woodard and Domenic Forte},
  journal= {arXiv preprint arXiv:2204.09579},
  year   = {2022}
}
R2 v1 2026-06-24T10:53:36.037Z