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Title: Leveraging Side-Channel Signals for Security and Trust
Nader Sehatbakhsh
Ph.D. Student
School of Computer Science
College of Computing
Georgia Institute of Technology
Date: Wednesday, November 6, 2019
Time: 13:00 - 15:00 (EST)
Location: Klaus 2100
Committee:
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Dr. Milos Prvulovic (Advisor, School of Computer Science, Georgia Institute of Technology)
Dr. Alenka Zajic (Co-Advisor, School of Electrical and Computer Engineering, Georgia Institute of Technology)
Dr. Angelos Keromytis (School of Electrical and Computer Engineering, Georgia Institute of Technology)
Dr. Hyesoon Kim (School of Computer Science, Georgia Institute of Technology)
Dr. Moin Qureshi (School of School of Electrical and Computer Engineering, Georgia Institute of Technology)
Abstract:
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With the proliferation of computing systems in our world, from servers to internet-of-things devices, side-channel signals have become significantly more available to measure and leverage. This availability provides both opportunities and security threats. On one hand, these side-channels may “leak” sensitive information about the system, and if exploited by an adversary, it would pose security threats to the system. On the other hand, however, these signals can be leveraged as extra sources of information which can be used for benign and useful purposes such as debugging/profiling, malware/intrusion detection, and security monitoring or code tracking. Given these opportunities and threats, understanding how these side-channels are created and developing frameworks to leverage them is an important topic.
To address these challenges, in this proposal, I will investigate new methods and frameworks to identify, quantify, and leverage side-channel signals particularly analog-domain electromagnetic (EM) emanations, and then describe how these analog-domain side-channels can be leveraged for intrusion detection on a variety of embedded and cyber-physical systems. Moreover, I will present our recent work on how side-channels can be leveraged to create a trusted execution environment (TEE) on a resource-constrained device (e.g., an Internet-of-Things device).
