Detection and analysis of eavesdropping in anonymous communication networks

2014 ◽  
Vol 14 (3) ◽  
pp. 205-220 ◽  
Author(s):  
Sambuddho Chakravarty ◽  
Georgios Portokalidis ◽  
Michalis Polychronakis ◽  
Angelos D. Keromytis
2019 ◽  
Vol 2019 (2) ◽  
pp. 105-125 ◽  
Author(s):  
Christiane Kuhn ◽  
Martin Beck ◽  
Stefan Schiffner ◽  
Eduard Jorswieck ◽  
Thorsten Strufe

Abstract Many anonymous communication networks (ACNs) with different privacy goals have been developed. Still, there are no accepted formal definitions of privacy goals, and ACNs often define their goals ad hoc. However, the formal definition of privacy goals benefits the understanding and comparison of different flavors of privacy and, as a result, the improvement of ACNs. In this paper, we work towards defining and comparing privacy goals by formalizing them as privacy notions and identifying their building blocks. For any pair of notions we prove whether one is strictly stronger, and, if so, which. Hence, we are able to present a complete hierarchy. Using this rigorous comparison between notions, we revise inconsistencies between the existing works and improve the understanding of privacy goals.


2020 ◽  
Vol 2020 (4) ◽  
pp. 111-130
Author(s):  
Lauren Watson ◽  
Anupam Mediratta ◽  
Tariq Elahi ◽  
Rik Sarkar

AbstractAnonymous communication networks like Tor are vulnerable to attackers that control entry and exit nodes. Such attackers can compromise the essential anonymity and privacy properties of the network. In this paper, we consider the path bias attack– where the attacker induces a client to use compromised nodes and thus links the client to their destination. We describe an efficient scheme that detects such attacks in Tor by collecting routing telemetry data from nodes in the network. The data collection is differentially private and thus does not reveal behaviour of individual users even to nodes within the network. We show provable bounds for the sample complexity of the scheme and describe methods to make it resilient to introduction of false data by the attacker to subvert the detection process. Simulations based on real configurations of the Tor network show that the method works accurately in practice.


Author(s):  
Michael Backes ◽  
Jeremy Clark ◽  
Aniket Kate ◽  
Milivoj Simeonovski ◽  
Peter Druschel

2020 ◽  
Vol 2020 (3) ◽  
pp. 356-383
Author(s):  
Debajyoti Das ◽  
Sebastian Meiser ◽  
Esfandiar Mohammadi ◽  
Aniket Kate

AbstractFor anonymous communication networks (ACNs), Das et al. recently confirmed a long-suspected trilemma result that ACNs cannot achieve strong anonymity, low latency overhead and low bandwidth overhead at the same time. Our paper emanates from the careful observation that their analysis does not include a relevant class of ACNs with what we call user coordination where users proactively work together towards improving their anonymity. We show that such protocols can achieve better anonymity than predicted by the above trilemma result. As the main contribution, we present a stronger impossibility result that includes all ACNs we are aware of. Along with our formal analysis, we provide intuitive interpretations and lessons learned. Finally, we demonstrate qualitatively stricter requirements for the Anytrust assumption (all but one protocol party is compromised) prevalent across ACNs.


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