Davide Rusconi (University of Milan), Osama Yousef (University of Milan), Mirco Picca (University of Milan), Danilo Bruschi (University of Milan), Flavio Toffalini (Ruhr-Universitat Bochum),  Andrea Lanzi (University of Milan)

In this paper, we show E-FuzzEdge, a novel fuzzing architecture targeted towards improving the throughput of fuzzing campaigns in contexts where scalability is unavailable. E-FuzzEdge addresses the inefficiencies of hardware-in-the-loop fuzzing for microcontrollers by optimizing execution speed. We evaluated our system against both real-world embedded libraries and state-of-the-art benchmarks, demonstrating significant performance improvements. A key advantage of the E-FuzzEdge architecture is its compatibility with other embedded fuzzing techniques that perform on device testing instead of firmware emulation. This means that the broader embedded fuzzing community can integrate E-FuzzEdge into their workflows to enhance overall testing efficiency.

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Private Yet Accurate: A Decentralized Approach to System Intrusion...

Jinghan Zhang (University of Virginia), Mati Ur Rehman (University of Virginia), Sharon Biju (University of Virginia), Saleha Muzammil (University of Virginia), Wajih Ul Hassan (University of Virginia)

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Beyond Conventional Triggers: Auto-Contextualized Covert Triggers for Android Logic...

Ye Wang (Department of Electrical Engineering and Computer Science, Institute for Information Sciences, The University of Kansas), Bo Luo (Department of Electrical Engineering and Computer Science, Institute for Information Sciences, The University of Kansas), Fengjun Li (Department of Electrical Engineering and Computer Science, Institute for Information Sciences, The University of Kansas)

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