Tootfinder

User Perceptions and Attitudes Toward Untraceability in Messaging Platforms
Carla F. Griggio, Boel Nelson, Zefan Sramek, Aslan Askarov
https://arxiv.org/abs/2506.11212

User Perceptions and Attitudes Toward Untraceability in Messaging Platforms
Mainstream messaging platforms offer a variety of features designed to enhance user privacy, such as disappearing messages, password-protected chats, and end-to-end encryption (E2EE), which primarily protect message contents. Beyond contents, the transmission of messages generates metadata that can reveal who communicates with whom, when and how often. In this paper, we study user perceptions of "untraceability", i.e., preventing third parties from tracing who communicates with whom, with the g…

Quantifying Mix Network Privacy Erosion with Generative Models
Vasilios Mavroudis, Tariq Elahi
https://arxiv.org/abs/2506.08918 https://

Quantifying Mix Network Privacy Erosion with Generative Models
Modern mix networks improve over Tor and provide stronger privacy guarantees by robustly obfuscating metadata. As long as a message is routed through at least one honest mixnode, the privacy of the users involved is safeguarded. However, the complexity of the mixing mechanisms makes it difficult to estimate the cumulative privacy erosion occurring over time. This work uses a generative model trained on mixnet traffic to estimate the loss of privacy when users communicate persistently over a per…