RAPTOR: Routing Attacks on Privacy in Tor
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Abstract (arXiv)
The Tor network is a widely used system for anonymous communication. However, Tor is known to be vulnerable to attackers who can observe traffic at both ends of the communication path. In this paper, we show that prior attacks are just the tip of the iceberg. We present a suite of new attacks, called Raptor, that can be launched by Autonomous Systems (ASes) to compromise user anonymity. First, AS-level adversaries can exploit the asymmetric nature of Internet routing to increase the chance of observing at least one direction of user traffic at both ends of the communication. Second, AS-level adversaries can exploit natural churn in Internet routing to lie on the BGP paths for more users over time. Third, strategic adversaries can manipulate Internet routing via BGP hijacks (to discover the users using specific Tor guard nodes) and interceptions (to perform traffic analysis). We demonstrate the feasibility of Raptor attacks by analyzing historical BGP data and Traceroute data as well as performing real-world attacks on the live Tor network, while ensuring that we do not harm real users. In addition, we outline the design of two monitoring frameworks to counter these attacks: BGP monitoring to detect control-plane attacks, and Traceroute monitoring to detect data-plane anomalies. Overall, our work motivates the design of anonymity systems that are aware of the dynamics of Internet routing.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Mar 2015.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 0; 2025: 1.
3 papers.
- 2021Jekyll: Attacking Medical Image Diagnostics using Deep Generative Modelscited by 10
- 2022SiamHAN: IPv6 Address Correlation Attacks on TLS Encrypted Traffic via Siamese Heterogeneous Graph Attention Networkcited by 1
- 2025How to Securely Shuffle? A survey about Secure Shufflers for privacy-preserving computationscited by 1
- 2025How to Securely Shuffle? A survey about Secure Shufflers for privacy-preserving computations2 Jul 2025
- 2022SiamHAN: IPv6 Address Correlation Attacks on TLS Encrypted Traffic via Siamese Heterogeneous Graph Attention Network20 Apr 2022
- 2021Jekyll: Attacking Medical Image Diagnostics using Deep Generative Models5 Apr 2021