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

April 19, 2022 ยท The Cartographer ยท ๐Ÿ› ACM Trans. Design Autom. Electr. Syst.

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
Survey/review paper โ€” maps the landscape rather than implementing a method.

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"Title-pattern auto-detect: A Survey and Perspective on Artificial Intelligence for Security-Aware Electronic Design Automation"

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Authors David Selasi Koblah, Rabin Yu Acharya, Daniel Capecci, Olivia P. Dizon-Paradis, Shahin Tajik, Fatemeh Ganji, Damon L. Woodard, Domenic Forte arXiv ID 2204.09579 Category cs.LG: Machine Learning Cross-listed cs.AI, cs.CR Citations 25 Venue ACM Trans. Design Autom. Electr. Syst. Last Checked 2 days ago
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.
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