DefWeb: Defending User Privacy against Cache-based Website Fingerprinting Attacks with Intelligent Noise Injection
Seonghun Son, Debopriya Roy Dipta, Berk Gülmezoğlu · Annual Computer Security Applications Conference · 2023
Cache-based website fingerprinting (WF) attacks violate user privacy where the attacker leverages the shared last-level cache in CPUs and analyzes the fingerprints through machine learning and deep learning models. WF attacks are even applicable in Incognito and anonymized browser platforms, leading to a serious threat to the public. Several defense techniques inject random noise during website rendering to degrade the attack success rate, while these techniques either create large performance overhead or cannot obfuscate the WF dataset entirely when the attacker retrains a new learning model with noisy fingerprints.