TOAR: Toward Resisting AS-Level Adversary Correlation Attacks Optimal Anonymous Routing

The Onion Router (Tor), as the most widely used anonymous network, is vulnerable to traffic correlation attacks by powerful passive adversaries, such as Autonomous Systems (AS). AS-level adversaries increase their chances of executing correlation attacks by manipulating the underlying routing, there...

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Main Authors: Hui Zhao, Xiangmei Song
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Mathematics
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Online Access:https://www.mdpi.com/2227-7390/12/23/3640
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author Hui Zhao
Xiangmei Song
author_facet Hui Zhao
Xiangmei Song
author_sort Hui Zhao
collection DOAJ
description The Onion Router (Tor), as the most widely used anonymous network, is vulnerable to traffic correlation attacks by powerful passive adversaries, such as Autonomous Systems (AS). AS-level adversaries increase their chances of executing correlation attacks by manipulating the underlying routing, thereby compromising anonymity. Furthermore, these underlying routing detours in the Tor client’s routing inference introduce extra latency. To address this challenge, we propose Toward Resisting AS-level Adversary Correlation Attacks Optimal Anonymous Routing (TOAR). TOAR is a two-stage routing mechanism based on Bayesian optimization within Software Defined Networks (SDN), comprising route search and route forwarding. Specifically, it searches for routes that conform to established policies, avoiding AS that could connect traffic between clients and destinations while maintaining anonymity in the selection of routes that minimize communication costs. To evaluate the anonymity of TOAR, as well as the effectiveness of route searching and the performance of route forwarding, we conduct a detailed analysis and extensive experiments. The analysis and experimental results show that the probability of routing being compromised by correlation attacks is significantly reduced. Compared to classical enumeration-based methods, the success rate of route searching increased by close to 2.5 times, and the forwarding throughput reached 70% of that of the packet transmission. The results show that TOAR effectively improves anonymity while maintaining communication quality, minimizing anonymity loss from AS-level adversaries and reducing high latency from routing detours.
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spelling doaj-art-2962525d2e974d709d498331c415263a2025-08-20T02:50:33ZengMDPI AGMathematics2227-73902024-11-011223364010.3390/math12233640TOAR: Toward Resisting AS-Level Adversary Correlation Attacks Optimal Anonymous RoutingHui Zhao0Xiangmei Song1School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, ChinaSchool of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, ChinaThe Onion Router (Tor), as the most widely used anonymous network, is vulnerable to traffic correlation attacks by powerful passive adversaries, such as Autonomous Systems (AS). AS-level adversaries increase their chances of executing correlation attacks by manipulating the underlying routing, thereby compromising anonymity. Furthermore, these underlying routing detours in the Tor client’s routing inference introduce extra latency. To address this challenge, we propose Toward Resisting AS-level Adversary Correlation Attacks Optimal Anonymous Routing (TOAR). TOAR is a two-stage routing mechanism based on Bayesian optimization within Software Defined Networks (SDN), comprising route search and route forwarding. Specifically, it searches for routes that conform to established policies, avoiding AS that could connect traffic between clients and destinations while maintaining anonymity in the selection of routes that minimize communication costs. To evaluate the anonymity of TOAR, as well as the effectiveness of route searching and the performance of route forwarding, we conduct a detailed analysis and extensive experiments. The analysis and experimental results show that the probability of routing being compromised by correlation attacks is significantly reduced. Compared to classical enumeration-based methods, the success rate of route searching increased by close to 2.5 times, and the forwarding throughput reached 70% of that of the packet transmission. The results show that TOAR effectively improves anonymity while maintaining communication quality, minimizing anonymity loss from AS-level adversaries and reducing high latency from routing detours.https://www.mdpi.com/2227-7390/12/23/3640anonymous routingBayesian optimizationcorrelation attacksSoftware Defined Network
spellingShingle Hui Zhao
Xiangmei Song
TOAR: Toward Resisting AS-Level Adversary Correlation Attacks Optimal Anonymous Routing
Mathematics
anonymous routing
Bayesian optimization
correlation attacks
Software Defined Network
title TOAR: Toward Resisting AS-Level Adversary Correlation Attacks Optimal Anonymous Routing
title_full TOAR: Toward Resisting AS-Level Adversary Correlation Attacks Optimal Anonymous Routing
title_fullStr TOAR: Toward Resisting AS-Level Adversary Correlation Attacks Optimal Anonymous Routing
title_full_unstemmed TOAR: Toward Resisting AS-Level Adversary Correlation Attacks Optimal Anonymous Routing
title_short TOAR: Toward Resisting AS-Level Adversary Correlation Attacks Optimal Anonymous Routing
title_sort toar toward resisting as level adversary correlation attacks optimal anonymous routing
topic anonymous routing
Bayesian optimization
correlation attacks
Software Defined Network
url https://www.mdpi.com/2227-7390/12/23/3640
work_keys_str_mv AT huizhao toartowardresistingasleveladversarycorrelationattacksoptimalanonymousrouting
AT xiangmeisong toartowardresistingasleveladversarycorrelationattacksoptimalanonymousrouting