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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Designing a Mobile App to Support Social Processes for...

Zaina Aljallad (University of Central Florida); Wentao Guo (Pomona College); Chhaya Chouhan, Christy Laperriere (University of Central Florida); Jess Kropczynski (University of Cincinnati); Pamela Wisnewski (University of Central Florida); Heather Lipford (University of North Carolina at Charlotte)

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TME-Box: Scalable In-Process Isolation through Intel TME-MK Memory Encryption

Martin Unterguggenberger (Graz University of Technology), Lukas Lamster (Graz University of Technology), David Schrammel (Graz University of Technology), Martin Schwarzl (Cloudflare, Inc.), Stefan Mangard (Graz University of Technology)

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Defending Against Membership Inference Attacks on Iteratively Pruned Deep...

Jing Shang (Beijing Jiaotong University), Jian Wang (Beijing Jiaotong University), Kailun Wang (Beijing Jiaotong University), Jiqiang Liu (Beijing Jiaotong University), Nan Jiang (Beijing University of Technology), Md Armanuzzaman (Northeastern University), Ziming Zhao (Northeastern University)

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Deanonymizing Device Identities via Side-channel Attacks in Exclusive-use IoTs...

Christopher Ellis (The Ohio State University), Yue Zhang (Drexel University), Mohit Kumar Jangid (The Ohio State University), Shixuan Zhao (The Ohio State University), Zhiqiang Lin (The Ohio State University)

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