Auditing Internet Content for Credibility, Fairness, and Privacy

This research is supported by the National Science Foundation.

Motivation and Approach

Millions of users are accessing a portion of billions of Web pages and other content on the Internet on a daily basis. While the networking research community and the public in general are well-aware of the net neutrality problem, i.e., how to develop regulatory policies and auditing mechanisms to prevent Internet Service Providers from discriminating against various applications, very little effort is invested in enabling content neutrality. In particular, it is not a secret that almost every browsing click we make is collected by either Web- or ISP-based "information collectors and aggregators", and that our profiles are used for online advertising. Still, no public auditing mechanisms, capable of detecting and informing end users about such practices, exist in this emerging area.

This project focuses on building a set of methodologies and tools capable of (i) enabling auditing mechanisms for the Web advertising domain, (ii) monitoring search engines' services and revealing their neutrality, and (iii) independently determining a Web site's popularity and checking for the truthfulness of advertised popularity.

People

Publications

  • Beating the Artificial Chaos: Fighting OSN Spam using Its Own Templates
    T. Zhu, H. Gao, Y. Yang, K. Bu, Y. Chen, D. Downey, K. Lee, and A. Choudhary
    In IEEE/ACM Transactions on Networking, 2016.
    [ .pdf ]

  • Energy and Performance of Smartphone Radio Bundling in Outdoor Environments
    A. Nika, Y. Zhu, N. Ding, A. Jindal, Y. Charlie Hu, X. Zhou, B. Zhao and H. Zheng
    In Proceedings of 24th International World Wide Web Conference, WWW 2015, Florence, Italy, May 2015.
    [ .pdf ]

  • Analyzing the Content Emphasis of Web Search Engines
    M. Alam and D. Downey
    In Proceedings of ACM SIGIR 2014, Golden Coast, Queensland, Australia, July 2014.
    [ .pdf ]
    Datasets are avalable here.

  • Measuring Web Servers' Popularity from an Endpoint
    A.-J. Su and A. Kuzmanovic
    Tech. Report NWU-EECS-15-03, Department of EECS, Northwestern University, October 2015.
    [ .pdf | .pdf.gz ]

  • How to Improve Your Search Enging Ranking: Myths and Reality
    A.-J. Su, Y. C. Hu, A. Kuzmanovic, and C.-K. Koh
    In ACM Transactions on the Web, Vol. 8, No. 2, Article 8, March 2014.
    [ .pdf ]
    An extended version of the WI 2010 paper.

  • Selective Behavior in Online Social Networks
    C. Xiao, L. Su, J. Bi, Y. Xue, and A. Kuzmanovic
    In IEEE/WIC/ACM International Conference on Web Intelligence, Macau, China, December 2012.
    [ .pdf | .pdf.gz | .ppt ]
    A large-scale analysis on disseminators and audiences properties in YouTube, Flickr and Twitter.

  • Understanding Crowds' Migration on the Web
    Y. Wang, K. Pal, and A. Kuzmanovic
    In IEEE/WIC/ACM International Conference on Web Intelligence, Lyon, France, August 2011.
    [ .pdf | .pdf.gz | .ppt ]
    A large-scale analysis on how users' interests collectively spread towards different Web sites.

  • Understanding the Network and User-Targeting Properties of Web Advertising Networks
    Y. Wang, D. Burgener, A. Kuzmanovic, and G. Macia
    In Proceedings of IEEE ICDCS 2011, Minneapolis, MN, June 2011.
    [ .pdf | .pdf.gz | .ppt ]
    The paper analyzes the properties of Web advertising networks.

  • How to Improve Your Google Ranking: Myths and Reality
    A.-J. Su, Y. C. Hu, A. Kuzmanovic, and C.-K. Koh
    In IEEE/WIC/ACM International Conference on Web Intelligence, Toronto, Canada, August 2010.
    [ .pdf | .pdf.gz | .ppt ]
    The paper presents a web-search auditing system.

  • Analyzing Content-Level Properties of the Web Adversphere
    Y. Wang, D. Burgener, A. Kuzmanovic, and G. Macia
    Poster paper in Proceedings of WWW 2010, Raleigh, NC, April 2010.
    [ .pdf | .pdf.gz | .ppt ]
    A short paper describing our initial efforts on building a content-level auditing service for web-based ad networks.