@inproceedings{2c13d913da3e42c8821e20af4fe57d2a,
title = "Traffic Analysis Attacks on Tor: A Survey",
abstract = "The Tor anonymity network is one of the most popular and widely used tools to protect the privacy of online users. Tor provides defenses against multiple adversarial activities aiming to identify or trace the users. Traffic analysis is a very strong tool that can be used for internet surveillance. Traffic analysis attacks against Tor's anonymity network has been known as an open question in research. Moreover, the low-latency feature Tor tries to provide to its users imposes limitations in defending against traffic analysis attacks. In our study, we examine traffic analysis attacks from the perspective of the adopted adversary model and how much it fits within Tor's threat model. The purpose of this study is to evaluate how practical these attacks are on real-time Tor network.",
keywords = "Anonymity Network, Attacks, Security, Tor, Traffic Analysis",
author = "Lamiaa Basyoni and Noora Fetais and Aiman Erbad and Amr Mohamed and Mohsen Guizani",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020 ; Conference date: 02-02-2020 Through 05-02-2020",
year = "2020",
month = feb,
doi = "10.1109/ICIoT48696.2020.9089497",
language = "English",
series = "2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "183--188",
booktitle = "2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020",
address = "United States",
}