Kevan Baker, Daniel R. Tauritz, Samuel Mulder (Auburn University)

Binary analysis tools work better together. In the case of static analysis, symbolic execution tools are used to explore possible execution paths in a binary and decompilers are used to view binary code. In this paper, we discuss the bridging of these two types of tools, using state-of-the-art tools Binary Ninja and angr. We present a work-in-progress plugin for Binary Ninja named Bangr which integrates features of angr. With our plugin, we demonstrate how coupling angr and Binary Ninja enables answering questions that Binary Ninja cannot answer on its own. We further demonstrate the utility of having a graphical interface for angr, and conclude with a discussion on the Bangr plugin.

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VICTOR: Dataset Copyright Auditing in Video Recognition Systems

Quan Yuan (Zhejiang University), Zhikun Zhang (Zhejiang University), Linkang Du (Xi'an Jiaotong University), Min Chen (Vrije Universiteit Amsterdam), Mingyang Sun (Peking University), Yunjun Gao (Zhejiang University), Shibo He (Zhejiang University), Jiming Chen (Zhejiang University and Hangzhou Dianzi University)

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Enabling Research Extensions in Matter via Custom Clusters

Ravindra Mangar (Dartmouth College, Hanover), Jared Chandler (Dartmouth College, Hanover), Timothy J. Pierson (Dartmouth College, Hanover), David Kotz (Dartmouth College, Hanover)

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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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