Quadruplet Fingerprinting: Onion Website Fingerprinting Through Quadruplet Network

The onion service is designed to achieve anonymity in the Tor network. However, it is highly vulnerable to website fingerprinting (WF) attacks because websites have unique traffic patterns that can be identified. Previous server-side WF attacks have certain limitations. There is an accuracy gap of nearly 10% when comparing with the ideal modeling using server-side traces. To address this issue, we propose a remote fingerprinting attack based on quadruplet networks, named Quadruplet Fingerprinting (QF). We utilize the RP node as the remote node and construct a feature extractor with quadruplet loss. This approach enhances the generalization ability of the model. The experimental results demonstrate that higher accuracy has been achieved in both common and few-shot WF scenarios compared to the existing methods. And most importantly, the accuracy rate of the RP side has been improved by more than 10% at the client side.