Abraham Clements, Abel Gomez Rivera (Sandia National Laboratories), Richard Jiayang Liu, Kirill Levchenko (University of Illinois Urbana-Champaign), Rick Kennell (Purdue University), Gabriela Ciocarlie (The Cybersecurity Manufacturing Innovation Institute and Stevens Institute of Technology) 

Embedded systems are integral to modern society and are increasingly being attacked, necessitating improved techniques to identifying and mitigating vulnerabilities. Fuzzing has proven to be a useful technique for identifying vulnerabilities. Nevertheless, the complexity of embedded systems using realtime operating systems (RTOSes) has limited the ability to even observe their execution, much less effectively fuzz them. Rehosting these systems’ firmware in an emulator has emerged as a technique to solve challenges with inspectability and parallelizing fuzzing, but challenges remain for complex RTOS-based systems. We present RT-Fuzzer, a technique that leverages the modularization of RTOS-based embedded systems into tasks to simplify re-hosting and enable effective feedback-directed fuzzing of complex embedded systems. RT-Fuzzer creates a custom initialization for the RTOS and core services in the emulator and then starts only the target task(s) for fuzzing. This simplifies rehosting and enables the fuzzing effort to be focused on a selected task. We illustrate this technique on an open source RTOS and a commercial PLC discovering and reporting vulnerabilities in both.

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DQN-IDS: A Deep Reinforcement Learning Approach for Open Set-Enabled...

Shreyash Tiwari (Computer and Information Science, University of Massachusetts Dartmouth), Nathaniel D. Bastian (Electrical Engineering and Computer Science, United States Military Academy), Gokhan Kul (Computer and Information Science, University of Massachusetts Dartmouth)

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Achieving Zen: Combining Mathematical and Programmatic Deep Learning Model...

David Oygenblik (Georgia Institute of Technology), Dinko Dermendzhiev (Georgia Institute of Technology), Filippos Sofias (Georgia Institute of Technology), Mingxuan Yao (Georgia Institute of Technology), Haichuan Xu (Georgia Institute of Technology), Runze Zhang (Georgia Institute of Technology), Jeman Park (Kyung Hee University), Amit Kumar Sikder (Iowa State University), Brendan Saltaformaggio (Georgia Institute of Technology)

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