Nothing Special   »   [go: up one dir, main page]

skip to main content
10.1145/3038912.3052587acmotherconferencesArticle/Chapter ViewAbstractPublication PagesthewebconfConference Proceedingsconference-collections
research-article

Who Controls the Internet?: Analyzing Global Threats using Property Graph Traversals

Published: 03 April 2017 Publication History

Abstract

The Internet is built on top of intertwined network services, e.g., email, DNS, and content distribution networks operated by private or governmental organizations. Recent events have shown that these organizations may, knowingly or unknowingly, be part of global-scale security incidents including state-sponsored mass surveillance programs and large-scale DDoS attacks. For example, in March 2015 the Great Cannon attack has shown that an Internet service provider can weaponize millions of Web browsers and turn them into DDoS bots by injecting malicious JavaScript code into transiting TCP connections.
While attack techniques and root cause vulnerabilities are routinely studied, we still lack models and algorithms to study the intricate dependencies between services and providers, reason on their abuse, and assess the attack impact. To close this gap, we present a technique that models services, providers, and dependencies as a property graph. Moreover, we present a taint-style propagation-based technique to query the model, and present an evaluation of our framework on the top 100k Alexa domains.

References

[1]
MaxMind: IP Geolocation and Online Fraud Prevention. http://dev.maxmind.com/.
[2]
RIPE Stat: Information about specific IP addresses and prefixes. https://stat.ripe.net/.
[3]
The New Threat: Targeted Internet Traffic Misdirection. http://research.dyn.com/2013/11/mitm-internet-hijacking/.
[4]
UK traffic diverted through Ukraine. http://research.dyn.com/2015/03/uk-traffic-diverted-ukraine/.
[5]
R. Albert, H. Jeong, and A.-L. Barabási. Error and attack tolerance of complex networks. nature, 406(6794):378--382, 2000.
[6]
K. R. Butler, T. R. Farley, P. McDaniel, and J. Rexford. A survey of bgp security issues and solutions. Proceedings of the IEEE, 98(1):100--122, 2010.
[7]
F. Cangialosi, T. Chung, D. R. Choffnes, D. Levin, B. M. Maggs, A. Mislove, and C. Wilson. Measurement and analysis of private key sharing in the HTTPS ecosystem. In Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, Vienna, Austria, October 24-28, 2016, pages 628--640, 2016.
[8]
R. Cohen, K. Erez, D. B. Avraham, and S. Havlin. Breakdown of the Internet under Intentional Attack. Physical Review Letters, 86(16):3682--3685, Apr. 2001.
[9]
L. Daigle. WHOIS Protocol Specification. RFC 3912 (Draft Standard), Sept. 2004.
[10]
S. Frey, Y. Elkhatib, A. Rashid, K. Follis, J. Vidler, N. Race, and C. Edwards. It bends but would it break? topological analysis of bgp infrastructures in europe. In 2016 IEEE European Symposium on Security and Privacy (Euro S&P 16), pages 423--438, March 2016.
[11]
E. Hjelmvik. China's man-on-the-side attack on github. http://bit.ly/2kx4zAE, 2015.
[12]
W. Jiang, D. Lee, and S. Hu. Large-scale longitudinal analysis of soap-based and restful web services. In Web Services (ICWS), 2012 IEEE 19th International Conference on, pages 218--225, June 2012.
[13]
S.-C. Kil, Hyunyoungand Oh, E. Elmacioglu, W. Nam, and D. Lee. Graph theoretic topological analysis of web service networks. World Wide Web, 12(3):321--343, 2009.
[14]
S. Landau. Making sense from snowden: What's significant in the nsa surveillance revelations. IEEE Security Privacy, 11(4):54--63, July 2013.
[15]
S. Liu, I. Foster, S. Savage, G. M. Voelker, and L. K. Saul. Who is .com?: Learning to parse whois records. In Proceedings of the 2015 ACM Conference on Internet Measurement Conference, IMC '15, pages 369--380, New York, NY, USA, 2015. ACM.
[16]
B. Marczak, N. Weaver, J. Dalek, R. Ensafi, D. Fifield, S. McKune, A. Rey, J. Scott-Railton, R. Deibert, and V. Paxson. An analysis of china great cannon. In 5th USENIX Workshop on Free and Open Communications on the Internet (FOCI 15), Washington, D.C., Aug. 2015. USENIX Association.
[17]
G. Nakibly, J. Schcolnik, and Y. Rubin. Website-targeted false content injection by network operators. In 25th USENIX Security Symposium (USENIX Security 16), pages 227--244, Austin, TX, Aug. 2016. USENIX Association.
[18]
A. Natarajan, P. Ning, Y. Liu, S. Jajodia, and S. E. Hutchinson. NSDMiner: Automated discovery of Network Service Dependencies. In Proceedings of the IEEE INFOCOM 2012, Orlando, FL, USA, March 25--30, 2012, pages 2507--2515, 2012.
[19]
J. Newland. Large scale ddos attack on github.com. https://github.com/blog/1981-large-scale-ddos-attack-on-github-com, 2015.
[20]
N. Nikiforakis, L. Invernizzi, A. Kapravelos, S. Van Acker, W. Joosen, C. Kruegel, F. Piessens, and G. Vigna. You are what you include: Large-scale evaluation of remote javascript inclusions. In Proceedings of the 2012 ACM Conference on Computer and Communications Security, CCS '12, pages 736--747, New York, NY, USA, 2012. ACM.
[21]
A. Noroozian, M. Korczyński, C. H. Ganan, D. Makita, K. Yoshioka, and M. van Eeten. Who Gets the Boot? Analyzing Victimization by DDoS-as-a-Service, pages 368--389. Springer International Publishing, Cham, 2016.
[22]
G. Pellegrino, C. Rossow, F. J. Ryba, T. C. Schmidt, and M. Wählisch. Cashing out the great cannon on browser-based ddos attacks and economics. In 9th USENIX Workshop on Offensive Technologies (WOOT 15), Washington, D.C., Aug. 2015. USENIX Association.
[23]
G. Pellegrino, C. Tschürtz, E. Bodden, and C. Rossow. jÄk: Using Dynamic Analysis to Crawl and Test Modern Web Applications, pages 295--316. Springer International Publishing, Cham, 2015.
[24]
D. A. Wheeler and G. N. Larsen. Techniques for cyber attack attribution. Technical report, DTIC Document, 2003.
[25]
A. Zand, G. Vigna, R. A. Kemmerer, and C. Kruegel. Rippler: Delay injection for service dependency detection. In 2014 IEEE Conference on Computer Communications, INFOCOM 2014, Toronto, Canada, April 27-May 2, 2014, pages 2157--2165, 2014.
[26]
J. Zhao, J. Wu, M. Chen, Z. Fang, X. Zhang, and K. Xu. K-core-based attack to the internet: Is it more malicious than degree-based attack? World Wide Web, 18(3):749--766, 2015.

Cited By

View all
  • (2024)Propagating Threat Scores with a TLS Ecosystem Graph Model Derived by Active Measurements2024 8th Network Traffic Measurement and Analysis Conference (TMA)10.23919/TMA62044.2024.10559063(1-11)Online publication date: 21-May-2024
  • (2024)The Times They Are A-Changin’: Characterizing Post-Publication Changes to Online News2024 IEEE Symposium on Security and Privacy (SP)10.1109/SP54263.2024.00033(1573-1589)Online publication date: 19-May-2024
  • (2024)A Comprehensive Evaluation of Machine Learning Algorithms for Web Application Attack Detection with Knowledge Graph IntegrationMobile Networks and Applications10.1007/s11036-024-02367-zOnline publication date: 19-Jul-2024
  • Show More Cited By

Index Terms

  1. Who Controls the Internet?: Analyzing Global Threats using Property Graph Traversals

    Recommendations

    Comments

    Please enable JavaScript to view thecomments powered by Disqus.

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    WWW '17: Proceedings of the 26th International Conference on World Wide Web
    April 2017
    1678 pages
    ISBN:9781450349130

    Sponsors

    • IW3C2: International World Wide Web Conference Committee

    In-Cooperation

    Publisher

    International World Wide Web Conferences Steering Committee

    Republic and Canton of Geneva, Switzerland

    Publication History

    Published: 03 April 2017

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. (dos) denial of service attacks
    2. cyber-attacks
    3. property graph traversals

    Qualifiers

    • Research-article

    Funding Sources

    • German Federal Ministry of Education and Research (BMBF)
    • project BOB

    Conference

    WWW '17
    Sponsor:
    • IW3C2

    Acceptance Rates

    WWW '17 Paper Acceptance Rate 164 of 966 submissions, 17%;
    Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)22
    • Downloads (Last 6 weeks)5
    Reflects downloads up to 28 Nov 2024

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)Propagating Threat Scores with a TLS Ecosystem Graph Model Derived by Active Measurements2024 8th Network Traffic Measurement and Analysis Conference (TMA)10.23919/TMA62044.2024.10559063(1-11)Online publication date: 21-May-2024
    • (2024)The Times They Are A-Changin’: Characterizing Post-Publication Changes to Online News2024 IEEE Symposium on Security and Privacy (SP)10.1109/SP54263.2024.00033(1573-1589)Online publication date: 19-May-2024
    • (2024)A Comprehensive Evaluation of Machine Learning Algorithms for Web Application Attack Detection with Knowledge Graph IntegrationMobile Networks and Applications10.1007/s11036-024-02367-zOnline publication date: 19-Jul-2024
    • (2023)Pareto-optimal Defenses for the Web Infrastructure: Theory and PracticeACM Transactions on Privacy and Security10.1145/356759526:2(1-36)Online publication date: 13-Mar-2023
    • (2023)The More Things Change, the More They Stay the Same: Integrity of Modern JavaScriptProceedings of the ACM Web Conference 202310.1145/3543507.3583395(2295-2305)Online publication date: 30-Apr-2023
    • (2023)A First Look at Third-Party Service Dependencies of Web Services in AfricaPassive and Active Measurement10.1007/978-3-031-28486-1_25(595-622)Online publication date: 21-Mar-2023
    • (2022)Leveraging Google’s Publisher-Specific IDs to Detect Website AdministrationProceedings of the ACM Web Conference 202210.1145/3485447.3512124(2522-2531)Online publication date: 25-Apr-2022
    • (2021)A Calculus of Tracking: Theory and PracticeProceedings on Privacy Enhancing Technologies10.2478/popets-2021-00272021:2(259-281)Online publication date: 29-Jan-2021
    • (2021)CHIEvACM SIGAPP Applied Computing Review10.1145/3477133.347713421:1(5-23)Online publication date: 20-Jul-2021
    • (2021)Mining Centralization of Internet Service Infrastructure in the Wild2021 17th International Conference on Mobility, Sensing and Networking (MSN)10.1109/MSN53354.2021.00060(341-349)Online publication date: Dec-2021
    • Show More Cited By

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media