Jack W. Davidson, Professor of Computer Science in the School of Engineering and Applied Science, University of Virginia

For the past twenty years, our research has been driven by the need to analyze, understand, and transform software without access to source code. Through a series of research programs, including DARPA’s Self-Regenerative Systems (SRS), AFOSR’s Enterprise Health: Self-Regenerative Incorruptible Enterprise program, IARPA’s Securely Taking on New Executable Software of Uncertain Provenance (STONESOUP) program, DARPA’s Cyber Grand Challenge (CGC), and DARPA’s Cyber Fault-Tolerant Attack and Recovery program (CFAR), and others, we have developed novel techniques to analyze and transform binaries. This talk will retrospectively examine these efforts and our key contributions in binary analysis and rewriting, from early vulnerability discovery techniques to advanced automated program transformations. We will also discuss current binary analysis research areas, speculate on where binary analysis research is heading, and why it continues to be an important, well-funded and impactful research area.

Speaker's Biography: Jack W. Davidson is a Professor of Computer Science in the School of Engineering and Applied Science at the University of Virginia. Professor Davidson is a Fellow of the ACM and a Life Fellow of the IEEE. He served as an Associate Editor of ACM’s Transactions on Programming Languages and Systems for six years, and as an Associate Editor of ACM’s Transactions on Architecture and Compiler Optimizations for eight years. He served as Chair of ACM’s Special Interest Group on Programming Languages (SIGPLAN) from 2005 to 2007. He currently serves on the ACM Executive Council and is chair of ACM’s Digital Library Board that oversees the operation and development of ACM’s Digital Library.

View More Papers

Evaluating Machine Learning-Based IoT Device Identification Models for Security...

Eman Maali (Imperial College London), Omar Alrawi (Georgia Institute of Technology), Julie McCann (Imperial College London)

Read More

QMSan: Efficiently Detecting Uninitialized Memory Errors During Fuzzing

Matteo Marini (Sapienza University of Rome), Daniele Cono D'Elia (Sapienza University of Rome), Mathias Payer (EPFL), Leonardo Querzoni (Sapienza University of Rome)

Read More

icLibFuzzer: Isolated-context libFuzzer for Improving Fuzzer Comparability

Yu-Chuan Liang, Hsu-Chun Hsiao (National Taiwan University)

Read More

ScopeVerif: Analyzing the Security of Android’s Scoped Storage via...

Zeyu Lei (Purdue University), Güliz Seray Tuncay (Google), Beatrice Carissa Williem (Purdue University), Z. Berkay Celik (Purdue University), Antonio Bianchi (Purdue University)

Read More