Taram wins ACM SIGMICRO Dissertation Award
Assistant Professor Mohammadkazem Taram
Congratulations to Assistant Professor Mohammadkazem Taram at Purdue University, Department of Computer Science for winning the 2023 ACM SIGMICRO Dissertation Award.
Assistant Professor Kazem Taram accepted the award at the 56th IEEE/ACM International Symposium on Microarchitecture. The title of Taram's dissertation is "Defusing the tension between security and performance with secure microarchitectures."
The SIGMICRO Outstanding Dissertation Award recognizes excellent thesis research by doctoral candidates in the field of computer microarchitecture. Dissertations are reviewed for technical depth and significance of the research contribution, potential impact, and quality of presentation. Taram is the inaugural winner of the dissertation award.
Advisor: Dean Tullsen
University of California San Diego, Computer Science & Engineering
The pursuit of secure computation has always featured a tension between performance and security. Security mitigations often come with a high performance cost that can be manifested in serious environmental and economic impacts if they are employed, and in disastrous security and privacy breaches, if not. In the context of processor architectures, the security-performance tension is only growing as new attacks appear, each exploiting a crucial performance optimization, threatening to unwind decades of architectural gains. These hosts of attacks on microarchitectural optimizations painfully coincide with an era in which those performance optimizations are needed most – an era when Moore’s law is fading and Denard’s scaling is gone.In this dissertation we strive to defuse this security-performance tension by deepening our understanding of vulnerabilities in modern processors, providing efficient hardware support to enable security, and designing new high-performance securearchitectures. We first show how performance optimizations can have devastating security implications by introducing a novel microarchitectural side-channel attack that targets Data Direct IO, a network packet processing optimization implemented by Intel (Chapter1). Then, we propose Context-Sensitive Decoding (CSD), a framework that takes advantage of the instruction-to-micro-op translation that exists in most modern processors to provide security features (Chapter2). Finally, we propose novel secure and fast architectures to mitigate vulnerabilities in two of the most crucial performance optimizations in modern processors: Speculative Execution (Chapter3)and Simultaneous Multithreading (Chapter4).