TY - CHAP A1 - Panchenko, Andriy A1 - Lanze, Fabian A1 - Zinnen, Andreas A1 - Henze, Martin A1 - Pennekamp, Jan A1 - Engel, Thomas A1 - Wehrle, Klaus T1 - Website Fingerprinting at Internet Scale T2 - Proceedings of the 23rd Internet Society (ISOC) Network and Distributed System Security Symposium (NDSS 2016), San Diego, USA, February 2016 Y1 - 2016 SN - 1-891562-41-X PB - Internet Society CY - Reston, VA ER - 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 - TY - GEN A1 - Pennekamp, Jan A1 - Henze, Martin A1 - Zinnen, Andreas A1 - Lanze, Fabian A1 - Wehrle, Klaus A1 - Panchenko, Andriy T1 - CUMUL & Co: High-Impact Artifacts for Website Fingerprinting Research T2 - 38th Annual Computer Security Applications Conference (ACSAC 2022), Austin, Texas, USA, December 5-9, 2022. N2 - Anonymous communication on the Internet is about hiding the relationship between communicating parties. At NDSS ’16, we presented a new website fingerprinting approach, CUMUL, that utilizes novel features and a simple yet powerful algorithm to attack anonymization networks such as Tor. Based on pattern observation of data flows, this attack aims at identifying the content of encrypted and anonymized connections. Apart from the feature generation and the used classifier, we also provided a large dataset to the research community to study the attack at Internet scale. In this paper, we emphasize the impact of our artifacts by analyzing publications referring to our work with respect to the dataset, feature extraction method, and source code of the implementation. Based on this data, we draw conclusions about the impact of our artifacts on the research field and discuss their influence on related cybersecurity topics. Overall, from 393 unique citations, we discover more than 130 academic references that utilize our artifacts, 61 among them are highly influential (according to SemanticScholar), and at least 43 are from top-ranked security venues. This data underlines the significant relevance and impact of our work as well as of our artifacts in the community and beyond. KW - Traffic Analysis;Website Fingerprinting; Privacy; Anonymous Communication; Onion Routing; Web Privacy Y1 - 2022 UR - https://www.acsac.org/2022/program/artifacts_competition/ ER -