Date: November 18, 2016
Speaker: Roman Lysecky (University of Arizona)
Location: DBH 6011
Time: 11am – 12pm
Host: Nikil Dutt
Title: Runtime Anomaly Detection (RAD)
Abstract: Networked embedded systems continue to pervade modern everyday activities at an accelerating pace. These systems find application in numerous critical infrastructures, including medical devices, autonomous vehicles, transportation systems, etc. The convergence of low-cost embedded hardware and ubiquitous network access has enabled increasingly pervasive environments, which are expected to seamlessly integrate with our social and commercial activities. Interconnecting multiple devices and enabling remote access comes with numerous security risks. Malicious software is growing at an alarming rate of approximately 100,000 new malware exploits per day. Historically, embedded systems were immune to malware, because they lacked network connectivity and were secured by their physical locations, but physical security cannot protect embedded systems that can be remotely accessed and controlled. Thus, a key component of embedded systems security is detection and identification of malware. In this talk, we present an overview of nonintrusive runtime anomaly detection (RAD) for detecting malware in embedded systems. The RAD approach uses formal time-centric system models that robustly capture the correct system execution behavior, and thereby enable efficient runtime detection of unauthorized system actions. The time-centric system model offer a unique opportunity to strengthen embedded system security by detecting subtle changes in the timing behavior of the system execution. We demonstrate that using such timing analysis, we can improve runtime malware detection capabilities.
Bio: Roman Lysecky is an Associate Professor of Electrical and Computer Engineering at the University of Arizona. He received his Ph.D. in Computer Science from the University of California, Riverside in 2005. His research interests focus on embedded systems, with emphasis on runtime optimization, non-intrusive system observation methods for in-situ analysis of complex hardware and software behavior, data-adaptable systems, and embedded systems security. He received the Outstanding Ph.D. Dissertation Award from the European Design and Automation Association (EDAA) in 2006, a CAREER award from the National Science Foundation in 2009, and five Best Paper Awards. He is an inventor on one US patent. He has coauthored six textbooks on C, C++, Java, Data Structures, VHDL, and Verilog, and he has contributed to several more. His recent textbooks with zyBooks utilize a web-native, active-learning approach that has shown measurable increases in student learning and course grades. He has also received multiple awards for Excellence at the Student Interface from the College of Engineering at the University of Arizona.
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