A Comprehensive Survey of Website Fingerprinting Attacks and Defenses in Tor: Advances and Open Challenges
This survey systematically categorizes website fingerprinting (WF) research in Tor into datasets, attacks, and defenses. It compares traditional ML and Deep Learning methods against techniques like adaptive padding and traffic morphing. The findings map out current strengths but highlight critical challenges such as model drift and multi-tab browsing complexity, guiding future privacy improvements.