CNS-1223477: TWC: Small: Knowing Your Enemy: Understanding and Counteracting Web Malvertising

Introduction

With the Internet becoming the dominant channel for marketing and promotion, online advertisements (ad for short) are also increasingly used for propagating malware, committing scams, click frauds and other illegal activities. This project endeavors to gain a holistic, in-depth understanding about the scope and magnitude of malicious advertising and related online illicit activities, features of their infrastructures, behavior of malicious parties, and economics of this underground business. Based upon such an understanding, we continue to develop novel infrastructure-aware technologies to detect those activities, such as effective analysis and detection techniques that identify malicious content, redirectors, advertisers, ad networks and other parties. This research involves industry collaborators and also contributes to understanding and mitigation of other security threats, using the new technologies developed as the result of the project.

Related paper

• S. Alrwais, K. Yuan, E. Alowaisheq, Z. Li and X. Wang, 2014 “Understanding the Dark Side of Domain Parking”. In Proceedings of the 23rd USENIX Security Symposium (Security).
• Z. Li, S. Alrwais, X. Wang and E. Alowaisheq, 2014 “Hunting the Red Fox Online: Understanding and Detection of Mass Redirect-Script Injections”. In Proceedings of the 35th IEEE Symposium on Security and Privacy (IEEE S&P)
• A. Zhang, X. Xie, K. Chang, C. Gunter, J. Han, X. Wang, 2014 “Privacy Risk in Anonymized Heterogeneous Information Networks”. In Proceedings of the 16th International Conference on Extending Database Technology (EDBT)
• Z. Li, S. Alrwais, Y. Xie, F. Yu and X. Wang, 2013 “Finding the Linchpins of the Dark Web: a Study on Topologically Dedicated Hosts on Malicious Web Infrastructures”. In Proceedings of the 34th IEEE Symposium on Security and Privacy (IEEE S&P)
• Z. Li, K. Zhang, Y. Xie, F. Yu and X. Wang, 2012 “Knowing Your Enemy: Understanding and Detecting Malicious Web Advertising”. In Proceedings of the 19th ACM Conference on Computer and Communications Security (CCS)

Patent

• Y. Xie, F. Yu, Z. Li and X. Wang, “Determining Legitimate and Malicious Advertisements Using Advertising Delivery Sequences”. Patent Application filed by Microsoft Research

Other Resources

• Under construction