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)

The fast-paced development and deployment of private messaging applications demands mechanisms to protect against the concomitant potential for abuse. While widely used end-to-end encrypted (E2EE) messaging systems have deployed mechanisms for users to verifiably report abusive messages without compromising the privacy of unreported messages, abuse reporting schemes for systems that additionally protect message metadata are still in their infancy. Existing solutions either focus on a relatively small portion of the design space or incur much higher communication and computation costs than their E2EE brethren.

This paper introduces new abuse reporting mechanisms that work for any private messaging system based on onion encryption. This includes low-latency systems that employ heuristic or opportunistic mixing of user traffic, as well as schemes based on mixnets. Along the way, we show that design decisions and abstractions that are well-suited to the E2EE setting may actually impede security and performance improvements in the metadata-hiding setting. We also explore stronger threat models for abuse reporting and moderation not explored in prior work, showing where prior work falls short and how to strengthen both our scheme and others'—including deployed E2EE messaging platforms—to achieve higher levels of security.

We implement a prototype of our scheme and find that it outperforms the best known solutions in this setting by well over an order of magnitude for each step of the message delivery and reporting process, with overheads almost matching those of message franking techniques used by E2EE encrypted messaging apps today.

View More Papers

BinEnhance: An Enhancement Framework Based on External Environment Semantics...

Yongpan Wang (Institute of Information Engineering Chinese Academy of Sciences & University of Chinese Academy of Sciences, China), Hong Li (Institute of Information Engineering Chinese Academy of Sciences & University of Chinese Academy of Sciences, China), Xiaojie Zhu (King Abdullah University of Science and Technology, Thuwal, Saudi Arabia), Siyuan Li (Institute of Information Engineering Chinese…

Read More

CLIBE: Detecting Dynamic Backdoors in Transformer-based NLP Models

Rui Zeng (Zhejiang University), Xi Chen (Zhejiang University), Yuwen Pu (Zhejiang University), Xuhong Zhang (Zhejiang University), Tianyu Du (Zhejiang University), Shouling Ji (Zhejiang University)

Read More

Privacy-Preserving Data Deduplication for Enhancing Federated Learning of Language...

Aydin Abadi (Newcastle University), Vishnu Asutosh Dasu (Pennsylvania State University), Sumanta Sarkar (University of Warwick)

Read More

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)

Read More