TY - GEN A1 - De la Cadena, Wladimir A1 - Kaiser, Daniel A1 - Mitseva, Asya A1 - Panchenko, Andriy A1 - Engel, Thomas ED - Foley, Simon N. T1 - Analysis of Multi-path Onion Routing-based Anonymization Networks T2 - Data and Applications Security and Privacy XXXIII : 33rd Annual IFIP WG 11.3 Conference, DBSec 2019, Charleston, SC, USA, July 15–17, 2019, Proceedings Y1 - 2019 UR - https://link.springer.com/book/10.1007%2F978-3-030-22479-0 SN - 978-3-030-22478-3 SN - 978-3-030-22479-0 U6 - https://doi.org/10.1007/978-3-030-22479-0_13 SN - 0302-9743 SN - 1611-3349 SP - 240 EP - 258 PB - Springer CY - Frankfurt am Main ER - TY - GEN A1 - Pennekamp, Jan A1 - Hiller, Jens A1 - Reuter, Sebastian A1 - De la Cadena, Wladimir A1 - Mitseva, Asya A1 - Henze, Martin A1 - Engel, Thomas A1 - Wehrle, Klaus A1 - Panchenko, Andriy T1 - Multipathing Traffic to Reduce Entry Node Exposure in Onion Routing T2 - Proceedings of the 27th annual IEEE International Conference on Network Protocols (Poster) (IEEE ICNP 2019), Chicago, Illinois, USA, October 2019 N2 - Users of an onion routing network, such as Tor, depend on its anonymity properties. However, especially malicious entry nodes, which know the client’s identity, can also observe the whole communication on their link to the client and, thus, conduct several de-anonymization attacks. To limit this exposure and to impede corresponding attacks, we propose to multipath traffic between the client and the middle node to reduce the information an attacker can obtain at a single vantage point. To facilitate the deployment, only clients and selected middle nodes need to implement our approach, which works transparently for the remaining legacy nodes. Furthermore, we let clients control the splitting strategy to prevent any external manipulation. Y1 - 2019 UR - https://ieeexplore.ieee.org/document/8888029 SN - 978-1-7281-2700-2 SN - 978-1-7281-2701-9 U6 - https://doi.org/10.1109/ICNP.2019.8888029 SN - 2643-3303 SN - 1092-1648 PB - IEEE Press ER - TY - GEN A1 - De la Cadena, Wladimir A1 - Mitseva, Asya A1 - Hiller, Jens A1 - Pennekamp, Jan A1 - Reuter, Sebastian A1 - Filter, Julian A1 - Engel, Thomas A1 - Wehrle, Klaus A1 - Panchenko, Andriy T1 - TrafficSliver: Fighting Website Fingerprinting Attacks with Traffic Splitting T2 - CCS '20: Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security, October 2020 N2 - Website fingerprinting (WFP) aims to infer information about the content of encrypted and anonymized connections by observing patterns of data flows based on the size and direction of packets. By collecting traffic traces at a malicious Tor entry node — one of the weakest adversaries in the attacker model of Tor — a passive eavesdropper can leverage the captured meta-data to reveal the websites visited by a Tor user. As recently shown, WFP is significantly more effective and realistic than assumed. Concurrently, former WFP defenses are either infeasible for deployment in real-world settings or defend against specific WFP attacks only. To limit the exposure of Tor users to WFP, we propose novel lightweight WFP defenses, TrafficSliver, which successfully counter today’s WFP classifiers with reasonable bandwidth and latency overheads and, thus, make them attractive candidates for adoption in Tor. Through user-controlled splitting of traffic over multiple Tor entry nodes, TrafficSliver limits the data a single entry node can observe and distorts repeatable traffic patterns exploited by WFP attacks.We first propose a network-layer defense, in which we apply the concept of multipathing entirely within the Tor network. We show that our network-layer defense reduces the accuracy from more than 98% to less than 16% for all state-of-the-art WFP attacks without adding any artificial delays or dummy traffic. We further suggest an elegant client-side application-layer defense, which is independent of the underlying anonymization network. By sending single HTTP requests for different web objects over distinct Tor entry nodes, our application-layer defense reduces the detection rate of WFP classifiers by almost 50 percentage points. Although it offers lower protection than our network-layer defense, it provides a security boost at the cost of a very low implementation overhead and is fully compatible with today's Tor network. KW - Traffic Analysis KW - Website Fingerprinting KW - Privacy KW - Anonymous Communication KW - Onion Routing KW - Web Privacy Y1 - 2020 SN - 978-1-4503-7089-9 U6 - https://doi.org/10.1145/3372297.3423351 SP - 1971 EP - 1985 PB - Association for Computing Machinery CY - New York ER - TY - GEN A1 - De la Cadena, Wladimir A1 - Kaiser, Daniel A1 - Panchenko, Andriy A1 - Engel, Thomas T1 - Out-of-the-box Multipath TCP as a Tor Transport Protocol: Performance and Privacy Implications T2 - 2020 IEEE 19th International Symposium on Network Computing and Applications (NCA), 24-27 Nov. 2020, Cambridge, MA, USA Y1 - 2020 SN - 978-1-7281-8326-8 SN - 978-1-7281-8327-5 U6 - https://doi.org/10.1109/NCA51143.2020.9306702 SN - 2643-7929 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 -