Tianchang Yang (Pennsylvania State University), Sathiyajith K S (Pennsylvania State University), Ashwin Senthil Arumugam (Pennsylvania State University), Syed Rafiul Hussain (Pennsylvania State University)

We present our work-in-progress on designing and implementing a black-box evolutionary fuzzer for REST APIs, specifically targeting 5G core networks that utilize a service-based architecture (SBA). Unlike existing tools that rely on static generation-based approaches, our approach progressively refines test inputs to explore deeper code regions in the target system. We incorporate a thorough analysis of the limited response message feedback available in black-box settings and employ a carefully crafted mutation method to generate effective state-aware test inputs. Evaluation of our current implementation has uncovered two previously unknown vulnerabilities in open-source 5G core network implementations, resulting in the assignment of two CVEs. Additionally, our approach already demonstrates superior performance compared to existing black-box fuzzing methods.

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BrowserFM: A Feature Model-based Approach to Browser Fingerprint Analysis

Maxime Huyghe (Univ. Lille, Inria, CNRS, UMR 9189 CRIStAL), Clément Quinton (Univ. Lille, Inria, CNRS, UMR 9189 CRIStAL), Walter Rudametkin (Univ. Rennes, Inria, CNRS, UMR 6074 IRISA)

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Onion Franking: Abuse Reports for Mix-Based Private Messaging

Matthew Gregoire (University of North Carolina at Chapel Hill), Margaret Pierce (University of North Carolina at Chapel Hill), Saba Eskandarian (University of North Carolina at Chapel Hill)

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Iris: Dynamic Privacy Preserving Search in Authenticated Chord Peer-to-Peer...

Angeliki Aktypi (University of Oxford), Kasper Rasmussen (University of Oxford)

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Retrofitting XoM for Stripped Binaries without Embedded Data Relocation

Chenke Luo (Wuhan University), Jiang Ming (Tulane University), Mengfei Xie (Wuhan University), Guojun Peng (Wuhan University), Jianming Fu (Wuhan University)

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