A Survey and Perspective on Artificial Intelligence for Security-Aware Electronic Design Automation
David Selasi Koblah, Rabin Yu Acharya, Daniel Capecci, Olivia P., Dizon-Paradis, Shahin Tajik, Fatemeh Ganji, Damon L. Woodard, Domenic Forte

TL;DR
This paper reviews how AI and machine learning are applied in electronic design automation, emphasizing security challenges and future research directions in security-aware IC design.
Contribution
It provides a comprehensive survey of AI/ML techniques in EDA, highlighting security issues and proposing future research directions for security-aware circuit design.
Findings
AI/ML enhances automation in IC design
Security concerns in AI-driven EDA are underexplored
Future research needed for security-aware design methods
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…
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Taxonomy
TopicsAdvancements in Semiconductor Devices and Circuit Design · Physical Unclonable Functions (PUFs) and Hardware Security · Advanced Memory and Neural Computing
