Zaid Hakami (Florida International University and Jazan University), Ashfaq Ali Shafin (Florida International University), Peter J. Clarke (Florida International University), Niki Pissinou (Florida International University), and Bogdan Carbunar (Florida International University)

Online abuse, a persistent aspect of social platform interactions, impacts user well-being and exposes flaws in platform designs that include insufficient detection efforts and inadequate victim protection measures. Ensuring safety in platform interactions requires the integration of victim perspectives in the design of abuse detection and response systems. In this paper, we conduct surveys (n = 230) and semi-structured interviews (n = 15) with students at a minority-serving institution in the US, to explore their experiences with abuse on a variety of social platforms, their defense strategies, and their recommendations for social platforms to improve abuse responses. We build on study findings to propose design requirements for abuse defense systems and discuss the role of privacy, anonymity, and abuse attribution requirements in their implementation. We introduce ARI, a blueprint for a unified, transparent, and personalized abuse response system for social platforms that sustainably detects abuse by leveraging the expertise of platform users, incentivized with proceeds obtained from abusers.

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PropertyGPT: LLM-driven Formal Verification of Smart Contracts through Retrieval-Augmented...

Ye Liu (Singapore Management University), Yue Xue (MetaTrust Labs), Daoyuan Wu (The Hong Kong University of Science and Technology), Yuqiang Sun (Nanyang Technological University), Yi Li (Nanyang Technological University), Miaolei Shi (MetaTrust Labs), Yang Liu (Nanyang Technological University)

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Secure IP Address Allocation at Cloud Scale

Eric Pauley (University of Wisconsin–Madison), Kyle Domico (University of Wisconsin–Madison), Blaine Hoak (University of Wisconsin–Madison), Ryan Sheatsley (University of Wisconsin–Madison), Quinn Burke (University of Wisconsin–Madison), Yohan Beugin (University of Wisconsin–Madison), Engin Kirda (Northeastern University), Patrick McDaniel (University of Wisconsin–Madison)

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Statically Discover Cross-Entry Use-After-Free Vulnerabilities in the Linux Kernel

Hang Zhang (Indiana University Bloomington), Jangha Kim (The Affiliated Institute of ETRI, ROK), Chuhong Yuan (Georgia Institute of Technology), Zhiyun Qian (University of California, Riverside), Taesoo Kim (Georgia Institute of Technology)

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Reinforcement Unlearning

Dayong Ye (University of Technology Sydney), Tianqing Zhu (City University of Macau), Congcong Zhu (City University of Macau), Derui Wang (CSIRO’s Data61), Kun Gao (University of Technology Sydney), Zewei Shi (CSIRO’s Data61), Sheng Shen (Torrens University Australia), Wanlei Zhou (City University of Macau), Minhui Xue (CSIRO's Data61)

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