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

Encrypted messaging systems provide end-to-end security for users but obstruct content moderation, making it difficult to combat online abuses. Traceability offers a promising solution by enabling platforms to identify the originator or spreader of messages, yet this capability can be abused for mass surveillance of innocent messages. To mitigate this risk, existing approaches restrict traceability to problematic messages that are reported by multiple users or are on a predefined blocklist. However, these solutions either over-trust a specific entity (e.g., the party defining the blocklist) or rely on the unrealistic assumption of non-collusion between servers run by a single platform.

In this paper, we propose an abuse-resistant source tracing scheme that distributes traceability across distinct real-world entities. Specifically, we formally define its syntax and prove its security properties. Our scheme realizes two essential principles: minimal trust, which ensures that traceability cannot be abused as long as a single participant involved in tracing is honest, even if all others collude; and minimal information disclosure, which prevents participants from acquiring any information (e.g., communication parties' identities) unnecessary for tracing. We implemented our scheme using techniques deployed by Signal, and our evaluation shows it offers comparable performance to state-of-the-art schemes that are vulnerable to abuse.

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Scalable Off-chain Auction

Mohsen Minaei (Visa Research), Ranjit Kumaresan (Visa Research), Andrew Beams (Visa Research), Pedro Moreno-Sanchez (IMDEA Software Institute, MPI-SP), Yibin Yang (Georgia Institute of Technology), Srinivasan Raghuraman (Visa Research and MIT), Panagiotis Chatzigiannis (Visa Research), Mahdi Zamani (Visa Research), Duc V. Le (Visa Research)

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VR ProfiLens: User Profiling Risks in Consumer Virtual Reality...

Ismat Jarin (University of California, Irvine), Olivia Figueira (University of California, Irvine), Yu Duan (University of California, Irvine), Tu Le (The University of Alabama), Athina Markopoulou (University of California, Irvine)

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Select-Then-Compute: Encrypted Label Selection and Analytics over Distributed Datasets...

Nirajan Koirala (University of Notre Dame), Seunghun Paik (Hanyang University), Sam Martin (University of Notre Dame), Helena Berens (University of Notre Dame), Tasha Januszewicz (University of Notre Dame), Jonathan Takeshita (Old Dominion University), Jae Hong Seo (Hanyang University), Taeho Jung (University of Notre Dame)

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