The classifier judged this item not relevant to AI security, so it is left out of lists, feeds, the API and dataset releases. If that is wrong, report a correction on this page.
Shift Your Shape: Correlating and Defending Mixnet Flows Based on Their Shapes
- Published
- Record updated
Summary
Researchers present a passive shape-based flow correlation attack against the Nym mixnet, assuming an adversary who controls both the entry and exit gateway-requesters. Their neural network scores flow pairs by traffic distribution similarity, reaching a PR-AUC of 0.9998 at a base rate of 1.9 × 10^-4 paired flow tuples after one minute of attacking default Nym. They also systematically evaluate five defense strategies, finding that the right choice and scale of countermeasures offers meaningful protection.
Mitigation
The authors evaluate five defense strategies and their combinations, and discuss steps a mixnet such as Nym can take to make the attack less likely and less accurate. The source does not list the specific steps in the text provided.