KIST

Author:

Jansen Rob1,Traudt Matthew1,Geddes John2,Wacek Chris3,Sherr Micah3,Syverson Paul1

Affiliation:

1. U.S. Naval Research Laboratory, DC, USA

2. University of Minnesota, MN, USA

3. Georgetown University, DC, USA

Abstract

Tor’s growing popularity and user diversity has resulted in network performance problems that are not well understood, though performance is understood to be a significant factor in Tor’s security. A large body of work has attempted to solve performance problems without a complete understanding of where congestion occurs in Tor. In this article, we first study congestion in Tor at individual relays as well as along the entire end-to-end Tor path and find that congestion occurs almost exclusively in egress kernel socket buffers. We then analyze Tor’s socket interactions and discover two major contributors to Tor’s congestion: Tor writes sockets sequentially, and Tor writes as much as possible to each socket. To improve Tor’s performance, we design, implement, and test KIST: a new socket management algorithm that uses real-time kernel information to dynamically compute the amount to write to each socket while considering all circuits of all writable sockets when scheduling cells. We find that, in the medians, KIST reduces circuit congestion by more than 30%, reduces network latency by 18%, and increases network throughput by nearly 10%. We also find that client and relay performance with KIST improves as more relays deploy it and as network load and packet loss rates increase. We analyze the security of KIST and find an acceptable performance and security tradeoff, as it does not significantly affect the outcome of well-known latency, throughput, and traffic correlation attacks. KIST has been merged and configured as the default socket scheduling algorithm in Tor version 0.3.2.1-alpha (released September 18, 2017) and became stable in Tor version 0.3.2.9 (released January 9, 2018). While our focus is Tor, our techniques and observations should help analyze and improve overlay and application performance, both for security applications and in general.

Funder

National Science Foundation

Defense Advanced Research Project Agency

Space and Naval Warfare Systems Center Pacific

Office of Naval Research

Department of Homeland Security (DHS) Science and Technology Directorate, Homeland Security Advanced Research Projects Agency, Cyber Security Division

Publisher

Association for Computing Machinery (ACM)

Subject

Safety, Risk, Reliability and Quality,General Computer Science

Reference65 articles.

1. Alessandro Acquisti Roger Dingledine and Paul Syverson. 2003. On the economics of anonymity. In Financial Cryptography and Data Security (FC). Alessandro Acquisti Roger Dingledine and Paul Syverson. 2003. On the economics of anonymity. In Financial Cryptography and Data Security (FC).

2. LASTor: A Low-Latency AS-Aware Tor Client

3. M. Allman V. Paxson and E. Blanton. 2009. TCP Congestion Control. RFC 5681 (Draft Standard). (Sept. 2009). http://www.ietf.org/rfc/rfc5681.txt. 10.17487/RFC2581 M. Allman V. Paxson and E. Blanton. 2009. TCP Congestion Control. RFC 5681 (Draft Standard). (Sept. 2009). http://www.ietf.org/rfc/rfc5681.txt. 10.17487/RFC2581

4. The Path Less Travelled: Overcoming Tor’s Bottlenecks with Traffic Splitting

5. Enhancing Tor's performance using real-time traffic classification

Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Performance or Anonymity? Source-Driven Tor Relay Selection for Performance Enhancement;2024 33rd International Conference on Computer Communications and Networks (ICCCN);2024-07-29

2. Exploring Reinforcement Learning to Aid Tor Latency Performance;2024 Silicon Valley Cybersecurity Conference (SVCC);2024-06-17

3. A Systematic Survey on Security in Anonymity Networks: Vulnerabilities, Attacks, Defenses, and Formalization;IEEE Communications Surveys & Tutorials;2024

4. QDRL: QoS-Aware Deep Reinforcement Learning Approach for Tor's Circuit Scheduling;IEEE Transactions on Network Science and Engineering;2022-09-01

5. ShorTor: Improving Tor Network Latency via Multi-hop Overlay Routing;2022 IEEE Symposium on Security and Privacy (SP);2022-05

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3