Tor is free software that enables anonymouscommunication. It defends users against traffic analysis andnetwork surveillance. It is also useful for confidential businessactivities and state security. At the same time, anonymizedprotocols have been used to access criminal websites such as thosedealing with illegal drugs. This paper proposes a new method forlaunching a fingerprinting attack to analyze Tor traffic in orderto detect users who access illegal websites. Our new method isbased on Stacked Denoising Autoencoder, a deep-learningtechnology. Our evaluation results show 0.88 accuracy in aclosed-world test. In an open-world test, the true positive rate is0.86 and the false positive rate is 0.02
