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Peek-a-Boo, I Still See You: Why Efficient Traffic Analysis Countermeasures Fail

Published: 20 May 2012 Publication History

Abstract

We consider the setting of HTTP traffic over encrypted tunnels, as used to conceal the identity of websites visited by a user. It is well known that traffic analysis (TA) attacks can accurately identify the website a user visits despite the use of encryption, and previous work has looked at specific attack/countermeasure pairings. We provide the first comprehensive analysis of general-purpose TA countermeasures. We show that nine known countermeasures are vulnerable to simple attacks that exploit coarse features of traffic (e.g., total time and bandwidth). The considered countermeasures include ones like those standardized by TLS, SSH, and IPsec, and even more complex ones like the traffic morphing scheme of Wright et al. As just one of our results, we show that despite the use of traffic morphing, one can use only total upstream and downstream bandwidth to identify--with 98% accuracy --which of two websites was visited. One implication of what we find is that, in the context of website identification, it is unlikely that bandwidth-efficient, general-purpose TA countermeasures can ever provide the type of security targeted in prior work.

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  • (2024)Safeguarding User-Centric Privacy in Smart HomesACM Transactions on Internet Technology10.1145/370172624:4(1-33)Online publication date: 18-Nov-2024
  • (2024)Defending Against Deep Learning-Based Traffic Fingerprinting Attacks With Adversarial ExamplesACM Transactions on Privacy and Security10.1145/369859128:1(1-23)Online publication date: 3-Oct-2024
  • (2024)Repositioning Real-World Website Fingerprinting on TorProceedings of the 23rd Workshop on Privacy in the Electronic Society10.1145/3689943.3695047(124-140)Online publication date: 20-Nov-2024
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Information

Published In

cover image Guide Proceedings
SP '12: Proceedings of the 2012 IEEE Symposium on Security and Privacy
May 2012
600 pages
ISBN:9780769546810

Publisher

IEEE Computer Society

United States

Publication History

Published: 20 May 2012

Author Tags

  1. encrypted traffic
  2. machine learning
  3. padding
  4. privacy
  5. traffic analysis countermeasures

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Cited By

View all
  • (2024)Safeguarding User-Centric Privacy in Smart HomesACM Transactions on Internet Technology10.1145/370172624:4(1-33)Online publication date: 18-Nov-2024
  • (2024)Defending Against Deep Learning-Based Traffic Fingerprinting Attacks With Adversarial ExamplesACM Transactions on Privacy and Security10.1145/369859128:1(1-23)Online publication date: 3-Oct-2024
  • (2024)Repositioning Real-World Website Fingerprinting on TorProceedings of the 23rd Workshop on Privacy in the Electronic Society10.1145/3689943.3695047(124-140)Online publication date: 20-Nov-2024
  • (2024)Understanding and Improving Video Fingerprinting Attack Accuracy under Challenging ConditionsProceedings of the 23rd Workshop on Privacy in the Electronic Society10.1145/3689943.3695045(141-154)Online publication date: 20-Nov-2024
  • (2024)VoiceAttack: Fingerprinting Voice Command on VPN-protected Smart Home SpeakersProceedings of the 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation10.1145/3671127.3698171(55-65)Online publication date: 29-Oct-2024
  • (2024)Let the Users Choose: Low Latency or Strong Anonymity? Investigating Mix Nodes with Paired Mixing TechniquesProceedings of the 19th International Conference on Availability, Reliability and Security10.1145/3664476.3664516(1-11)Online publication date: 30-Jul-2024
  • (2024)Contrastive Fingerprinting: A Novel Website Fingerprinting Attack over Few-shot TracesProceedings of the ACM Web Conference 202410.1145/3589334.3645575(1203-1214)Online publication date: 13-May-2024
  • (2023)Subverting website fingerprinting defenses with robust traffic representationProceedings of the 32nd USENIX Conference on Security Symposium10.5555/3620237.3620272(607-624)Online publication date: 9-Aug-2023
  • (2023)Enhancing the Unlinkability of Circuit-Based Anonymous Communications with k-FunnelsProceedings of the ACM on Networking10.1145/36291401:CoNEXT3(1-26)Online publication date: 28-Nov-2023
  • (2023)Prediction Privacy in Distributed Multi-Exit Neural Networks: Vulnerabilities and SolutionsProceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security10.1145/3576915.3623069(1123-1137)Online publication date: 15-Nov-2023
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