TY - GEN A1 - Panchenko, Andriy A1 - Mitseva, Asya A1 - Ziemann, Torsten A1 - Hering, Till T1 - GuardedGossip: Secure and Anonymous Node Discovery in Untrustworthy Networks T2 - Security and Privacy in Communication Networks : 17th EAI International Conference, SecureComm 2021, Virtual Event, September 6–9, 2021, Proceedings, Part I N2 - Node discovery is a fundamental service for any overlay network. It is a particular challenge to provide unbiased discovery in untrustworthy environments, e.g., anonymization networks. Although a major line of research focused on solving this problem, proposed methods have been shown to be vulnerable either to active attacks or to leak routing information, both threatening the anonymity of users. In response, we propose GuardedGossip—a novel gossip-based node discovery protocol—that achieves an unbiased random node discovery in a fully-decentralized and highly-scalable fashion. It is built on top of a Chord distributed hash table (DHT) and relies on witness nodes and bound checks to resist active attacks. To limit routing information leakages, GuardedGossip uses gossiping to create uncertainty in the process of node discovery. By incorporating the principles of DHTs with the unstructured nature of gossiping in a subtle way, we profit from the strengths of both techniques while carefully mitigating their shortcomings. We show that GuardedGossip provides a sufficient level of security for users even if 20% of the participating nodes are malicious. Concurrently, our system scales gracefully and provides an adequate overhead for its security and privacy benefits. KW - Node lookup KW - DHT KW - Tor KW - Onion routing KW - Anonymity Y1 - 2021 SN - 978-3-030-90018-2 U6 - https://doi.org/10.1007/978-3-030-90019-9_7 SN - 1867-8211 SP - 123 EP - 143 PB - Springer CY - Cham ER - TY - GEN A1 - Mitseva, Asya A1 - Panchenko, Andriy T1 - Stop, don't click here anymore: boosting website fingerprinting by considering sets of subpages T2 - Proceedings of the 33rd USENIX Security Symposium (USENIX Sec 2024), Philadelphia, PA, USA, August 14-16, 2024 N2 - A type of traffic analysis, website fingerprinting (WFP), aims to reveal the website a user visits over an encrypted and anonymized connection by observing and analyzing data flow patterns. Its efficiency against anonymization networks such as Tor has been widely studied, resulting in methods that have steadily increased in both complexity and power. While modern WFP attacks have proven to be highly accurate in laboratory settings, their real-world feasibility is highly debated. These attacks also exclude valuable information by ignoring typical user browsing behavior: users often visit multiple pages of a single website sequentially, e.g., by following links. In this paper, we aim to provide a more realistic assessment of the degree to which Tor users are exposed to WFP. We propose both a novel WFP attack and efficient strategies for adapting existing methods to account for sequential visits of pages within a website. While existing WFP attacks fail to detect almost any website in real-world settings, our novel methods achieve F1-scores of 1.0 for more than half of the target websites. Our attacks remain robust against state-of- the-art WFP defenses, achieving 2.5 to 5 times the accuracy of prior work, and in some cases even rendering the defenses useless. Our methods enable to estimate and to communicate to the user the risk of successive page visits within a website (even in the presence of noise pages) to stop before the WFP attack reaches a critical level of confidence. Y1 - 2024 UR - https://www.usenix.org/system/files/usenixsecurity24-mitseva.pdf UR - https://dblp.org/rec/conf/uss/Mitseva024.html SN - 978-1-939133-44-1 SP - 4139 EP - 4156 ER - TY - GEN A1 - Mitseva, Asya A1 - Alexandrova, Marharyta A1 - Panchenko, Andriy T1 - Security and Performance Implications of BGP Rerouting-resistant Guard Selection Algorithms for Tor T2 - Computers and Security N2 - Tor is the most popular anonymization network with millions of daily users. This makes it an attractive target for attacks, e.g., by malicious autonomous systems (ASs) performing active routing attacks to become man in the middle and deanonymize users. It was shown that the number of such malicious ASs is significantly larger than previously expected due to the lack of security guarantees in the Border Gateway Protocol (BGP). In response, recent works suggest alternative Tor path selection methods preferring Tor nodes with higher resilience to active BGP attacks. In this work, we analyze the implications of such proposals and demonstrate that two state-of-the-art path selection methods, namely Counter-RAPTOR and DPSelect, are not as secure as thought before. First, we show that DPSelect achieves only one third of its originally claimed resilience and, thus, is not as resilient as widely accepted. Second, we reveal that the resilience to active BGP attacks on the way back, i.e., from the first anonymization node to a given Tor user, provided by both methods is significantly lower than on the forward path. Beside their lower resilience in specific cases, we show that for particular users the usage of Counter-RAPTOR and DPSelect also leads to leakage of user’s location. Furthermore, we uncover the performance implications of both methods and identify scenarios where their usage leads to significant performance bottlenecks. Finally, we propose a new metric to quantify the user’s location leakage by path selection. Using this metric and performing large-scale analysis, we show to which extent a malicious Tor middle node can fingerprint the user’s location and the confidence it can achieve. Our findings shed light on the implications of path selection methods on the users’ anonymity and the need for further research. KW - BGP routing attacks KW - Tor KW - Onion routing KW - Privacy KW - Traffic analysis Y1 - 2023 U6 - https://doi.org/10.1016/j.cose.2023.103374 SN - 1872-6208 SN - 0167-4048 VL - 132 ER - TY - GEN A1 - Mitseva, Asya A1 - Thierse, Paul A1 - Hoffmann, Harald A1 - Er, Devran A1 - Panchenko, Andriy ED - Katsikas, Sokratis T1 - Challenges and Pitfalls in Generating Representative ICS Datasets in Cyber Security Research T2 - Computer Security, ESORICS 2022 International Workshops CyberICPS 2022, SECPRE 2022, SPOSE 2022, CPS4CIP 2022, CDT&SECOMANE 2022, EIS 2022, and SecAssure 2022 Copenhagen, Denmark, September 26–30, 2022, Revised Selected Papers Y1 - 2023 SN - 978-3-031-25459-8 SN - 978-3-031-25460-4 U6 - https://doi.org/10.1007/978-3-031-25460-4_22 SP - 379 EP - 397 PB - Springer International Publishing CY - Cham ER - TY - THES A1 - Mitseva, Asya T1 - State of affairs in online user privacy : assessing real-world user information leakages and designing effective and practical countermeasures T1 - Aktueller Stand der Privatsphäre von Internetnutzern : Bewertung realer Datenlecks und Entwicklung wirksamer und praktischer Gegenmaßnahmen N2 - The Tor network ensures confidentiality of user data over the Internet and hides the IP addresses and relationships between communication partners to avoid user profiling and censorship. However, Tor cannot hide the number, direction, and timing of transmitted packets. Two types of attackers – autonomous systems (AS) and malicious Tor nodes – can exploit this for sophisticated attacks, such as website fingerprinting (WFP) and end-to-end traffic correlation, or fingerprinting attacks revealing the Tor users’ location. On the other hand, in case of a malicious first Tor node or a malicious AS on the path between the user and the Tor network, the scalability of prior WFP attacks remains questionable due to impractical assumptions. This dissertation aims to provide a more realistic assessment of the exposure of Tor users to passive deanonymization attacks from different perspectives. First, we conduct a comprehensive review of fundamental Border Gateway Protocol (BGP) threats. We present a methodology for evaluating existing BGP security proposals and provide an extensive and up-to-date survey of proposals intended to make BGP secure and methods for detecting and mitigating routing instabilities. Based on the identified research gaps and unresolved challenges, we analyze the current level of resilience of Tor and two alternative Tor path selection methods against malicious ASs. While we detect a notable increase in the Tor’s resilience to BGP attacks over the years, when measured from a Tor user to its first Tor node, the resilience provided by the alternative path selection methods on the way back, i.e., from the first Tor node to a Tor user, has decreased notably compared to the resilience measured on the forward path for these methods. Moreover, these methods tend to select first Tor nodes in a predictable manner, resulting in the exposure of users’ locations to Tor middle nodes. We also show novel attacks against a state-of-the-art method for measuring bandwidth capabilities of Tor nodes, allowing a low-bandwidth attacker to gain notably higher bandwidth estimates than theoretically defined. We propose a novel lightweight defense against malicious Tor nodes, performing WFP or end-to-end traffic correlation, that splits user traffic over multiple Tor paths. Our defense is fully implemented on the user side, reducing deployment costs and making it independent of the underlying anonymization network. We also propose a metric that is capable of quantifying the user’s location leakage considering a malicious Tor middle node. This metric enables Tor users to avoid specific first Tor nodes by strategically selecting those from which their location cannot be revealed. Finally, we examine the real-world scalability of WFP, especially against Tor users who visit several pages of a single website consecutively. We propose both a novel WFP attack and efficient strategies for adapting existing methods to account for sequential visits of pages within a website. KW - Anonyme Kommunikation KW - Border Gateway Protocol (BGP KW - Datenschutz im Internet KW - Datenverkehrsanalyse KW - Onion routing; Tor network KW - Traffic analysis KW - Website fingerprinting KW - Website fingerprinting defenses Y1 - 2025 U6 - https://doi.org/10.26127/BTUOpen-7214 PB - Brandenburgische Technische Universität CY - Cottbus-Senftenberg ER - TY - GEN A1 - Mitseva, Asya A1 - Lewandowsky, Marco A1 - Panchenko, Andriy T1 - Poster: characterization of dominant and specific network patterns in industrial control systems T2 - 2025 23rd International Symposium on Network Computing and Applications (NCA) N2 - The increasing digitization and interconnection of Industrial Control Systems (ICS) to the Internet render them susceptible to cyber attacks. Thus, a major line of research focuses on the design of reactive security solutions in the form of industrial intrusion detection systems, which aim to detect anomalies in a normal system operation. However, a crucial prerequisite for the accurate detection and localization of anomalies is the identification of typical traffic patterns that are exclusive to characterize the normal ICS behavior. Unlike previous work focusing on complex and protocol-dependent models, for characterizing ICS network traffic, in this work we propose simple, easy deployable, and effective rules for determining whether ICS network traffic, unlike traditional IT networks, remains stable over time. The main advantage of our rules is that they can be used to estimate the time required to identify the most dominant ICS traffic patterns in a given ICS. We show the efficacy of our rules by analyzing multiple ICS datasets with different industrial network protocols. KW - Industrial Control Systems KW - Traffic Patterns Y1 - 2025 SN - 979-8-3315-7842-8 U6 - https://doi.org/10.1109/NCA67271.2025.00059 SP - 314 EP - 315 PB - IEEE CY - Piscataway, NJ ER - TY - GEN A1 - Mitseva, Asya A1 - Lewandowsky, Marco A1 - Panchenko, Andriy ED - Skwarek, Volker ED - Wöhnert, Kai Hendrik ED - Kaven, Sascha ED - Wendzel, Steffen T1 - Whitelisting als Allheilmittel : über die Grenzen der Anomalieerkennung in industriellen Steuerungssystemen T2 - Sicherheit 2026 : Sicherheit, Schutz und Zuverlässigkeit, 17.-19. März 2026, Hamburg : proceedings N2 - Die zunehmende Digitalisierung und Vernetzung industrieller Steuerungssysteme mit dem Internet macht diese anfällig für Cyberangriffe. Ein zentraler Forschungsbereich konzentriert sich daher auf die Entwicklung reaktiver Sicherheitsmechanismen in Form industrieller Intrusion-Detection-Systeme (IIDS), die darauf ausgelegt sind, Anomalien im normalen Systembetrieb zu erkennen. Eine entscheidende Voraussetzung hierfür ist die Identifizierung typischer Verkehrsmuster, die ausschließlich für das normale Verhalten industrieller Steuerungssysteme charakteristisch sind. Im Gegensatz zu früheren Arbeiten, die sich auf komplexe und protokollabhängige Modelle zur Charakterisierung des Netzwerkverkehrs industrieller Steuerungssysteme konzentrierten, schlagen wir in dieser Arbeit einfache, leicht umsetzbare und effektive Regeln vor, um zu ermitteln, ob der Netzwerkverkehr in Industrieanlagen – im Gegensatz zu herkömmlichen IT-Netzwerken – über einen längeren Zeitraum stabil bleibt. Anhand der Analyse mehrerer Datensätze aus nachgebildeten und realen industriellen Steuerungssystemen mit unterschiedlichen industriellen Netzwerkprotokollen zeigen wir, dass aufbauend auf diesen Regeln bereits nach kurzer Beobachtungszeit hinreichend prägnante Muster extrahiert werden können, mit deren Hilfe es möglich ist, gängige Verkehrsveränderungen durch Netzverkehrsangriffe zu erkennen. Dieser Ansatz steht im Gegensatz zu herkömmlichen Machine-Learning-IIDS, die häufig einen beträchtlichen zeitlichen Aufwand für den Trainingsprozess erfordern. Somit stellen wir auch die Frage auf, inwieweit komplexe IIDS für den praktischen Betrieb tatsächlich unabdingbar sind. KW - Steuerungssysteme KW - Datenverkehrsmuster KW - Datensätze KW - Intrusion-Detection-Systeme Y1 - 2026 UR - https://dl.gi.de/items/7b5e1e96-dad3-4843-aca7-77593cd8ddde U6 - https://doi.org/10.18420/sicherheit2026_09 SN - 2944-7682 SP - 103 EP - 114 PB - Gesellschaft für Informatik CY - Bonn ER -