% % This file was created by the TYPO3 extension % bib % --- Timezone: CEST % Creation date: 2024-10-16 % Creation time: 02-57-34 % --- Number of references % 2 % @Inproceedings { 2020_delacadena_trafficsliver, title = {TrafficSliver: Fighting Website Fingerprinting Attacks with Traffic Splitting}, year = {2020}, month = {11}, day = {12}, pages = {1971-1985}, abstract = {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.}, keywords = {Traffic Analysis; Website Fingerprinting; Privacy; Anonymous Communication; Onion Routing; Web Privacy}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2020/2020-delacadena-trafficsliver.pdf}, web_url = {https://github.com/TrafficSliver}, publisher = {ACM}, booktitle = {Proceedings of the 27th ACM SIGSAC Conference on Computer and Communications Security (CCS '20), November 9-13, 2020, Orlando, FL, USA}, event_place = {Virtual Event, USA}, event_date = {November 9-13, 2020}, ISBN = {978-1-4503-7089-9/20/11}, DOI = {10.1145/3372297.3423351}, reviewed = {1}, author = {De la Cadena, Wladimir and Mitseva, Asya and Hiller, Jens and Pennekamp, Jan and Reuter, Sebastian and Filter, Julian and Wehrle, Klaus and Engel, Thomas and Panchenko, Andriy} } @Inproceedings { 2020-henze-ccs-cybersecurity, title = {Poster: Cybersecurity Research and Training for Power Distribution Grids -- A Blueprint}, year = {2020}, month = {11}, day = {9}, abstract = {Mitigating cybersecurity threats in power distribution grids requires a testbed for cybersecurity, e.g., to evaluate the (physical) impact of cyberattacks, generate datasets, test and validate security approaches, as well as train technical personnel. In this paper, we present a blueprint for such a testbed that relies on network emulation and power flow computation to couple real network applications with a simulated power grid. We discuss the benefits of our approach alongside preliminary results and various use cases for cybersecurity research and training for power distribution grids.}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2020/2020-henze-ccs-cybersecurity.pdf}, publisher = {ACM}, address = {New York, NY, USA}, booktitle = {Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security (CCS ’20), November 9–13, 2020, Virtual Event, USA.}, event_place = {Virtual Event, USA}, event_date = {November 9-13, 2020}, DOI = {10.1145/3372297.3420016}, reviewed = {1}, author = {Henze, Martin and Bader, Lennart and Filter, Julian and Lamberts, Olav and Ofner, Simon and van der Velde, Dennis} }