TY - GEN A1 - Mitseva, Asya A1 - Panchenko, Andriy A1 - Lanze, Fabian A1 - Henze, Martin A1 - Engel, Thomas A1 - Wehrle, Klaus T1 - POSTER: Fingerprinting Tor Hidden Services T2 - In Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security (CCS '16). Association for Computing Machinery, New York, NY, USA Y1 - 2016 SN - 978-1-4503-4139-4 U6 - https://doi.org/10.1145/2976749.2989054 SP - 1766 EP - 1768 PB - ACM CY - New York ER - TY - CHAP A1 - Panchenko, Andriy A1 - Mitseva, Asya A1 - Henze, Martin A1 - Lanze, Fabian A1 - Engel, Thomas A1 - Wehrle, Klaus T1 - Analysis of Fingerprinting Techniques for Tor Hidden Services T2 - WPES '17 Proceedings of the 2017 on Workshop on Privacy in the Electronic Society, Dallas, Texas, USA, October 2017 Y1 - 2017 SN - 978-1-4503-5175-1 U6 - https://doi.org/10.1145/3139550.3139564 SP - 165 EP - 175 PB - ACM CY - New York, NY ER - TY - GEN A1 - De La Cadena, Wladimir A1 - Mitseva, Asya A1 - Pennekamp, Jan A1 - Hiller, Jens A1 - Lanze, Fabian A1 - Engel, Thomas A1 - Wehrle, Klaus A1 - Panchenko, Andriy T1 - POSTER: Traffic Splitting to Counter Website Fingerprinting T2 - CCS '19 Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security , London, UK, November 11 - 15, 2019. N2 - Website fingerprinting (WFP) is a special type of traffic analysis, which aims to infer the websites visited by a user. Recent studies have shown that WFP targeting Tor users is notably more effective than previously expected. Concurrently, state-of-the-art defenses have been proven to be less effective. In response, we present a novel WFP defense that splits traffic over multiple entry nodes to limit the data a single malicious entry can use. Here, we explore several traffic-splitting strategies to distribute user traffic. We establish that our weighted random strategy dramatically reduces the accuracy from nearly 95% to less than 35% for four state-of-the-art WFP attacks without adding any artificial delays or dummy traffic. Y1 - 2019 UR - https://dl.acm.org/citation.cfm?doid=3319535.3363249 SN - 978-1-4503-6747-9 U6 - https://doi.org/10.1145/3319535.3363249 SP - 2533 EP - 2535 PB - ACM Press CY - New York ER -