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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Impact Tracing: Identifying the Culprit of Misinformation in Encrypted...

Zhongming Wang (Chongqing University), Tao Xiang (Chongqing University), Xiaoguo Li (Chongqing University), Biwen Chen (Chongqing University), Guomin Yang (Singapore Management University), Chuan Ma (Chongqing University), Robert H. Deng (Singapore Management University)

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Understanding Data Importance in Machine Learning Attacks: Does Valuable...

Rui Wen (CISPA Helmholtz Center for Information Security), Michael Backes (CISPA Helmholtz Center for Information Security), Yang Zhang (CISPA Helmholtz Center for Information Security)

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Detecting IMSI-Catchers by Characterizing Identity Exposing Messages in Cellular...

Tyler Tucker (University of Florida), Nathaniel Bennett (University of Florida), Martin Kotuliak (ETH Zurich), Simon Erni (ETH Zurich), Srdjan Capkun (ETH Zuerich), Kevin Butler (University of Florida), Patrick Traynor (University of Florida)

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