More Web Proxy on the site http://driver.im/

research-article

What can you learn from an IP?

Authors:

Nikita BorisovAuthors Info & Claims

ANRW '19: Proceedings of the 2019 Applied Networking Research Workshop

Pages 45 - 51

https://doi.org/10.1145/3340301.3341133

Published: 22 July 2019 Publication History

Abstract

The Internet was not designed with security in mind. A number of recent protocols such as Encrypted DNS, HTTPS, etc. target encrypting critical parts of the web architecture, which can otherwise be exploited by eavesdroppers to infer users' data. But encryption may not necessarily guarantee privacy, especially when it comes to metadata. Emerging standards can protect the contents of both DNS queries and the TLS SNI extensions; however, it might still be possible to determine which websites users are visiting by simply looking at the destination IP addresses on the traffic originating from users' devices. We perform a measurement study to determine the anonymity provided by IP addresses resulting from the multiple sub-queries that are made as a consequence of accessing a particular web page. We show that, in most cases, an adversary can use the IP addresses during a page load as a form of a fingerprint to infer the original site identity.

References

[1]

Sara Dickinson, Daniel Kahn Gillmor, and K Tirumaleswar Reddy. 2018. Usage Profiles for DNS over TLS and DNS over DTLS. RFC 8310.

[2]

Adrienne Porter Felt, Richard Barnes, April King, Chris Palmer, Chris Bentzel, and Parisa Tabriz. 2017. Measuring {HTTPS} Adoption on the Web. In 26th {USENIX} Security Symposium ({USENIX} Security 17). 1323--1338.

Digital Library

[3]

David Fifield, Chang Lan, Rod Hynes, Percy Wegmann, and Vern Paxson. 2015. Blocking-resistant communication through domain fronting. Proceedings on Privacy Enhancing Technologies 2015, 2 (2015), 46--64.

[4]

Paweł Foremski, Christian Callegari, and Michele Pagano. 2014. DNS-Class: immediate classification of IP flows using DNS. International Journal of Network Management 24, 4 (2014), 272--288.

Digital Library

[5]

Google. {n.d.}. Chrome User Experience Report. https://developers.google.com/web/tools/chrome-user-experience-report/.

[6]

Paul E. Hoffman and Patrick McManus. 2018. DNS Queries over HTTPS (DoH). RFC 8484.

Digital Library

[7]

IETF. {n.d.}. Transport Layer Security (TLS) Extensions: Extension Definitions. https://tools.ietf.org/html/rfc6066.

[8]

Hongbo Jiang, Andrew W Moore, Zihui Ge, Shudong Jin, and Jia Wang. 2007. Lightweight application classification for network management. In Proceedings of the 2007 SIGCOMM workshop on Internet networkmanagement. ACM, 299--304.

Digital Library

[9]

B. Laurie, A. Langley, and E. Kasper. 2013. Certificate Transparency. RFC 6962. RFC Editor.

[10]

Paul Murley. {n.d.}. MIDA: A Tool for Measuring the Web. https://mida.sprai.org/.

[11]

Eric Rescorla. 2018. The Transport Layer Security (TLS) Protocol Version 1.3. RFC 8446.

[12]

Eric Rescorla, Kazuho Oku, Nick Sullivan, and Christopher A. Wood. 2018. Encrypted Server Name Indication for TLS 1.3. Internet-Draft draftietf-tls-esni-02. Internet Engineering Task Force. https://datatracker.ietf.org/doc/html/draft-ietf-tls-esni-02 Work in Progress.

[13]

Mahrud Sayrafi. 2018. Introducing DNS Resolver for Tor. https://blog.cloudflare.com/welcome-hidden-resolver/.

[14]

Amazon Web Services. {n.d.}. Alexa Top Sites. https://aws.amazon.com/alexa-top-sites/.

[15]

Davide Tammaro, Silvio Valenti, Dario Rossi, and Antonio Pescapé. 2012. Exploiting packet-sampling measurements for traffic characterization and classification. International Journal of Network Management 22, 6 (2012), 451--476.

Digital Library

[16]

Martino Trevisan, Idilio Drago, Marco Mellia, and Maurizio M Munafo. 2016. Towards web service classification using addresses and DNS. In 2016 International Wireless Communications and Mobile Computing Conference (IWCMC). IEEE, 38--43.

[17]

Turbobytes. {n.d.}. cdnfinder. https://github.com/turbobytes/cdnfinder.

Cited By

Xue NMalla YXia ZPöpper CVanhoef MCalandrino JTroncoso C(2023)Bypassing tunnelsProceedings of the 32nd USENIX Conference on Security Symposium10.5555/3620237.3620557(5719-5736)Online publication date: 9-Aug-2023
https://dl.acm.org/doi/10.5555/3620237.3620557
Schepers DRanganathan AVanhoef MCalandrino JTroncoso C(2023)Framing framesProceedings of the 32nd USENIX Conference on Security Symposium10.5555/3620237.3620241(53-68)Online publication date: 9-Aug-2023
https://dl.acm.org/doi/10.5555/3620237.3620241
Ardi CHussain ACollins MSchwab STashtarian FTimmerer CLiotou EDasari M(2022)Improving fidelity in video streaming experimentation on testbeds with a CDNProceedings of the 2nd International Workshop on Design, Deployment, and Evaluation of Network-Assisted Video Streaming10.1145/3565476.3569097(1-7)Online publication date: 9-Dec-2022
https://dl.acm.org/doi/10.1145/3565476.3569097
Show More Cited By

Recommendations

TCP-Jersey for wireless IP communications

Improving the performance of the transmission control protocol (TCP) in wireless Internet protocol (IP) communications has been an active research area. The performance degradation of TCP in wireless and wired-wireless hybrid networks is mainly due to ...
TCP/IP Protocol Suite
Congestion control in TCP/IP networks: a combined ECN and BECN approach
MILCOM'03: Proceedings of the 2003 IEEE conference on Military communications - Volume I

In this paper a novel algorithm is proposed which combines the merits of Explicit Congestion Notification (ECN) and Backward Explicit Congestion Notification (BECN) mechanisms for congestion control in TCP/IP networks. A comparative performance ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

ANRW '19: Proceedings of the 2019 Applied Networking Research Workshop

July 2019

80 pages

ISBN:9781450368483

DOI:10.1145/3340301

Program Chairs:
Phillipa Gill
University of Massachusetts-Amherst
,
Jana Iyengar
Fastly

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Sponsors

SIGCOMM: ACM Special Interest Group on Data Communication

In-Cooperation

IRTF: Internet Research Task Force
Internet Society: Internet Society

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 July 2019

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Qualifiers

Research-article

Conference

ANRW '19

Sponsor:

SIGCOMM

ANRW '19: Applied Networking Research Workshop

July 22, 2019

Quebec, Montreal, Canada

Acceptance Rates

Overall Acceptance Rate 34 of 58 submissions, 59%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

10
Total Citations
View Citations
661
Total Downloads

Downloads (Last 12 months)45
Downloads (Last 6 weeks)2

Reflects downloads up to 15 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Xue NMalla YXia ZPöpper CVanhoef MCalandrino JTroncoso C(2023)Bypassing tunnelsProceedings of the 32nd USENIX Conference on Security Symposium10.5555/3620237.3620557(5719-5736)Online publication date: 9-Aug-2023
https://dl.acm.org/doi/10.5555/3620237.3620557
Schepers DRanganathan AVanhoef MCalandrino JTroncoso C(2023)Framing framesProceedings of the 32nd USENIX Conference on Security Symposium10.5555/3620237.3620241(53-68)Online publication date: 9-Aug-2023
https://dl.acm.org/doi/10.5555/3620237.3620241
Ardi CHussain ACollins MSchwab STashtarian FTimmerer CLiotou EDasari M(2022)Improving fidelity in video streaming experimentation on testbeds with a CDNProceedings of the 2nd International Workshop on Design, Deployment, and Evaluation of Network-Assisted Video Streaming10.1145/3565476.3569097(1-7)Online publication date: 9-Dec-2022
https://dl.acm.org/doi/10.1145/3565476.3569097
Bhargavan KCheval VWood CYin HStavrou ACremers CShi E(2022)A Symbolic Analysis of Privacy for TLS 1.3 with Encrypted Client HelloProceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security10.1145/3548606.3559360(365-379)Online publication date: 7-Nov-2022
https://dl.acm.org/doi/10.1145/3548606.3559360
Izhikevich LAkiwate GBerger BDrakontaidis SAscheman APearce PAdrian DDurumeric ZBarakat CPelsser CBenson TChoffnes D(2022)ZDNSProceedings of the 22nd ACM Internet Measurement Conference10.1145/3517745.3561434(33-43)Online publication date: 25-Oct-2022
https://dl.acm.org/doi/10.1145/3517745.3561434
Hoang NNiaki AGill PPolychronakis M(2021)Domain name encryption is not enough: privacy leakage via IP-based website fingerprintingProceedings on Privacy Enhancing Technologies10.2478/popets-2021-00782021:4(420-440)Online publication date: 23-Jul-2021
https://doi.org/10.2478/popets-2021-0078
Csikor LSingh HKang MDivakaran D(2021)Privacy of DNS-over-HTTPS: Requiem for a Dream?2021 IEEE European Symposium on Security and Privacy (EuroS&P)10.1109/EuroSP51992.2021.00026(252-271)Online publication date: Sep-2021
https://doi.org/10.1109/EuroSP51992.2021.00026
Di Martino MQuax PLamotte W(2020)Knocking on IPsSecurity and Communication Networks10.1155/2020/72857862020Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1155/2020/7285786
Hoang NAkhavan Niaki ABorisov NGill PPolychronakis MSun HShieh SGu GAteniese G(2020)Assessing the Privacy Benefits of Domain Name EncryptionProceedings of the 15th ACM Asia Conference on Computer and Communications Security10.1145/3320269.3384728(290-304)Online publication date: 5-Oct-2020
https://dl.acm.org/doi/10.1145/3320269.3384728
Komosny DRehman S(2020)Survival Analysis and Prediction Model of IP Address Assignment DurationIEEE Access10.1109/ACCESS.2020.30217608(162507-162515)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3021760

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents