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AuthorBasyoni L.
AuthorFetais N.
AuthorErbad A.
AuthorMohamed A.
AuthorGuizani M.
Available date2022-04-21T08:58:26Z
Publication Date2020
Publication Name2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020
ResourceScopus
Identifierhttp://dx.doi.org/10.1109/ICIoT48696.2020.9089497
URIhttp://hdl.handle.net/10576/30103
AbstractThe 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. 2020 IEEE.
SponsorQatar Foundation;Qatar National Research Fund
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectNetwork security
Adversary modeling
Anonymity networks
Internet surveillances
Online users
Threat modeling
Tor networks
Traffic analysis
Traffic analysis attacks
Internet of things
TitleTraffic Analysis Attacks on Tor: A Survey
TypeConference Paper
Pagination183-188


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