Yoshiya Ikezaki

Papers

Total Citations

H-Index

About

Yoshiya Ikezaki is a researcher at the forefront of hardware security and edge AI, specializing in the intersection of embedded systems and trustworthy computing. His work addresses critical vulnerabilities in AI hardware, particularly focusing on hardware Trojans (HTs) that can compromise FPGA-based AI modules used in automotive and robotic systems. His most cited paper, "LUT oriented Hardware Trojan for FPGA based AI Module" (2020, 8 citations), introduces a novel attack vector targeting look-up tables in reconfigurable architectures, revealing how malicious modifications can subvert AI inference at the hardware level. This contribution is pivotal for understanding security risks in edge AI deployment, where trustworthiness is paramount for real-world applications. Ikezaki’s research bridges the gap between hardware security and AI reliability, offering insights into countermeasures for emerging threats. His work is particularly relevant for students and engineers developing secure embedded AI systems, as it highlights the often-overlooked vulnerabilities in hardware implementations. With a growing citation impact, Ikezaki is establishing himself as a key voice in the evolving field of hardware-aware AI security.