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Break-Pad: effective padding machines for tor with break burst padding.
- Source :
- Cybersecurity (2523-3246); 10/1/2024, Vol. 7 Issue 1, p1-18, 18p
- Publication Year :
- 2024
-
Abstract
- Website Fingerprinting (WF) attacks enable a local eavesdropper to use metadata of packet flow, such as size, timing, and direction, to infer the websites a user is visiting. This can damage the user privacy provided by anonymity systems such as Tor. Tor has implemented the WF defense called Circuit Padding Framework, which provides an interface for developers to implement their own defenses. However, these defenses in the framework were overcome by the Deep Fingerprinting (DF) attack. In this paper, we propose a novel defense approach called break burst padding (Break-Pad), which injects a random number of padding packets into an incoming burst once the number of consecutive incoming packets exceeds a set number. We integrated Break-Pad into the existing Circuit Padding Framework. In addition, we have implemented two padding machines named August and October in the new framework and conducted experiments to evaluate these machines. In the open-world setting, our results show that August, with 29% bandwidth overhead, reduces Tik-Tok's TPR by 14.48% and DF's TPR by 22%. October outperforms the best padding machine, RBB. With 36% bandwidth overhead, it drops Tik-Tok's TPR to 74.24% and DF's TPR to 65.36%. In the one-page setting, October further reduces the bandwidth overhead by 11% while achieving similar performance to RBB. In the information leak analysis, for the burst sequence feature of the traffic, October leaks at 2.453 bits, while the best comparable padding machine Interspace leaks at 2.629 bits. [ABSTRACT FROM AUTHOR]
- Subjects :
- LEAKS (Disclosure of information)
RANDOM numbers
METADATA
BANDWIDTHS
WEBSITES
Subjects
Details
- Language :
- English
- ISSN :
- 25233246
- Volume :
- 7
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Cybersecurity (2523-3246)
- Publication Type :
- Academic Journal
- Accession number :
- 180005988
- Full Text :
- https://doi.org/10.1186/s42400-024-00222-y