Website Fingerprinting - Last Level Cache Contention Traces

Website fingerprinting attacks, which use statistical analysis on network traffic to compromise user privacy, have been shown to be effective even if the traffic is sent over anonymity-preserving networks such as Tor. The classical attack model used to evaluate website fingerprinting attacks assumes an on-path adversary, who can observe all traffic traveling between the user's computer and the secure network.

Dataset Files

You must be an IEEE Dataport Subscriber to access these files. Subscribe now or login.

[1] , "Website Fingerprinting - Last Level Cache Contention Traces", IEEE Dataport, 2019. [Online]. Available: http://dx.doi.org/10.21227/a33s-cf63. Accessed: Sep. 22, 2019.
@data{a33s-cf63-19,
doi = {10.21227/a33s-cf63},
url = {http://dx.doi.org/10.21227/a33s-cf63},
author = { },
publisher = {IEEE Dataport},
title = {Website Fingerprinting - Last Level Cache Contention Traces},
year = {2019} }
TY - DATA
T1 - Website Fingerprinting - Last Level Cache Contention Traces
AU -
PY - 2019
PB - IEEE Dataport
UR - 10.21227/a33s-cf63
ER -
. (2019). Website Fingerprinting - Last Level Cache Contention Traces. IEEE Dataport. http://dx.doi.org/10.21227/a33s-cf63
, 2019. Website Fingerprinting - Last Level Cache Contention Traces. Available at: http://dx.doi.org/10.21227/a33s-cf63.
. (2019). "Website Fingerprinting - Last Level Cache Contention Traces." Web.
1. . Website Fingerprinting - Last Level Cache Contention Traces [Internet]. IEEE Dataport; 2019. Available from : http://dx.doi.org/10.21227/a33s-cf63
. "Website Fingerprinting - Last Level Cache Contention Traces." doi: 10.21227/a33s-cf63