MixFlow: Assessing Mixnets Anonymity with Contrastive Architectures and Semantic Network Information

ePrint Report: MixFlow: Assessing Mixnets Anonymity with Contrastive Architectures and Semantic Network Information

Reyhane Attarian, Esfandiar Mohammadi, Tao Wang, Emad Heydari Beni

In this paper, we propose the MixFlow model, an approach for analyzing the unobservability and unlinkability of instant messaging in Loopix Mix networks. The MixFlow model utilizes contrastive architectures and loss functions inspired by DNA sequence analysis in bioinformatics to identify semantic relationships between entry and exit flows, even after applying significant transformations such as poisson mixing delay …

analysis anonymity dna entry eprint report exit functions identify information instant messaging loss messaging network networks relationships report tao