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Anonymity networks are becoming increasingly popular in todays online world as more users attempt to safeguard their online privacy. Tor is currently the most popular anonymity network in use and provides anonymity to both users and services (hidden services). However, the anonymity provided by Tor is also being misused in various ways. Hosting illegal sites for selling drugs, hosting command and control servers for botnets, and distributing censored content are but a few such examples. As a result, various parties, including governments and law enforcement agencies, are interested in attacks that assist in de-anonymising the Tor network, disrupting its operations, and bypassing its censorship circumvention mechanisms. In this paper, we survey known Tor attacks and identify currently available techniques that lead to improved de-anonymisation of users and hidden services.
The Tor anonymity system provides online privacy for millions of users, but it is slower than typical web browsing. To improve Tor performance, we propose PredicTor, a path selection technique that uses a Random Forest classifier trained on recent me
This is a short note that formally presents the matching model for the theoretical study of self-adjusting networks as initially proposed in [1].
Some BitTorrent users are running BitTorrent on top of Tor to preserve their privacy. In this extended abstract, we discuss three different attacks to reveal the IP address of BitTorrent users on top of Tor. In addition, we exploit the multiplexing o
In this work we show that Tor is vulnerable to app deanonymization attacks on Android devices through network traffic analysis. For this purpose, we describe a general methodology for performing an attack that allows to deanonymize the apps running o
Anonymity has become a significant issue in security field by recent advances in information technology and internet. The main objective of anonymity is hiding and concealing entities privacy inside a system. Many methods and protocols have been prop