Hardware Fuzzing to Secure Modern Hardware

Hardware is at the heart of computing systems. However, recent years have seen increased attacks exploiting hardware vulnerabilities and exploits, which even traditional software-based protections cannot prevent. Hardware fuzzing has shown promise in detecting vulnerabilities in large-scale designs like modern processors. In this talk, I will describe the hardware vulnerabilities in hardware description languages, such as Verilog and VHDL. Then, I will explain a new and radical approach called hardware fuzzing to find these vulnerabilities and detail how fuzzing techniques can be combined with existing formal verification techniques to detect vulnerabilities efficiently. Finally, I will discuss a strategy for pinpointing vulnerabilities to accelerate the mitigation process and briefly talk about improving the efficiency of hardware fuzzing using ML/AI techniques, such as multi-armed bandit (MAB) and large language models (LLM).

Mr. Rahul Kande is a Ph.D. student in the Computer Engineering and Systems Group at Texas A&M University since 2018. He completed his Bachelor of Technology in Electronics and Communication Engineering from the Indian Institute of Technology Guwahati in 2017. He developed TheHuzz, a novel hardware fuzzer that detected new vulnerabilities in popular open-source processors. This work received great traction in the industry and academia, especially Intel and the Office of Naval Research (ONR), USA, who are now jointly funding their future fuzzing projects. Rahul has won several awards and scholarships during his Ph.D. program, such as the departmental Quality Graduate Student Award in 2023 and Graduate Merit Scholarship in 2018, 3rd place at IEEE HOST 2022 Hardware Demonstration, and USENIX Security Symposium Student Grant in 2020 and 2021. His research involves developing more efficient and automated hardware fuzzing techniques to detect vulnerabilities in hardware, especially processors.