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[PAST EVENT] Haitao Xu - Ph.D. Defense - Computer Science
April 9, 2015
10am - 12pm
Abstract:
The continuous expansion of the Internet in the past 20 years has greatly facilitated the booming development of Internet business. Unfortunately, some unscrupulous participants in Internet business conduct fraudulent activities for their own profits at the expense of other parties. In this proposal, we present our study on the fraudulent activities in two kinds of major Internet businesses---online advertising and E-commerce.
Online advertising is leveraged by online advertisers to deliver marketing messages to potential customers. It serves as a significant source of revenue for web-based businesses and is crucial to a thriving Internet ecosystem. However, click fraud is posing a serious threat to online advertising systems. As the direct victims, advertisers still lack effective defense against click fraud. In this proposal, we present a novel approach for advertisers to detect click fraud without the helps from ad networks or publishers. Our proposed defense is effective in identifying both clickbots and human clickers, while incurring negligible overhead at both the server and client sides.
In an E-commerce market, a store's reputation is closely tied to its profitability. Sellers' desire to quickly achieve high reputation has fueled a profitable underground business, termed by us as a seller-reputation-escalation (SRE) market. An SRE market operates as a specialized crowdsourcing marketplace and facilitates online sellers to harness human laborers to conduct fake transactions for improving their stores' reputations. In this proposal, we characterize the SRE markets in terms of its prevalence, business model, market size, and the sellers and laborers involved. We also evaluate the effectiveness of the SRE services on reputation escalation.
An online photo could disclose much more information beyond what is visually depicted in the photo and what its owner expects to share. In the future work, we plan to explore the potential privacy threats arising from sharing digital photos online. We will first investigate the prevalence of privacy information among digital photos. Then we introduce an attack vector not exploited before and demonstrate its surprising power in identifying a photographer with just one photo she ever took. Finally, we will build a proof-of-concept tool to alert users on potential privacy disclosure.
Bio:
Haitao Xu received his Bachelor of Science in Computer Science from Zhengzhou University, Zhengzhou, China in 2007 and Master of Engineering in Computer Science from University of Chinese Academy of Sciences, Beijing, China in 2010. He is currently pursuing Ph.D. degree in the Department of Computer Science at the College of William & Mary. His research interests lie in Web Security, Online Fraud Detection and Network Security.
The continuous expansion of the Internet in the past 20 years has greatly facilitated the booming development of Internet business. Unfortunately, some unscrupulous participants in Internet business conduct fraudulent activities for their own profits at the expense of other parties. In this proposal, we present our study on the fraudulent activities in two kinds of major Internet businesses---online advertising and E-commerce.
Online advertising is leveraged by online advertisers to deliver marketing messages to potential customers. It serves as a significant source of revenue for web-based businesses and is crucial to a thriving Internet ecosystem. However, click fraud is posing a serious threat to online advertising systems. As the direct victims, advertisers still lack effective defense against click fraud. In this proposal, we present a novel approach for advertisers to detect click fraud without the helps from ad networks or publishers. Our proposed defense is effective in identifying both clickbots and human clickers, while incurring negligible overhead at both the server and client sides.
In an E-commerce market, a store's reputation is closely tied to its profitability. Sellers' desire to quickly achieve high reputation has fueled a profitable underground business, termed by us as a seller-reputation-escalation (SRE) market. An SRE market operates as a specialized crowdsourcing marketplace and facilitates online sellers to harness human laborers to conduct fake transactions for improving their stores' reputations. In this proposal, we characterize the SRE markets in terms of its prevalence, business model, market size, and the sellers and laborers involved. We also evaluate the effectiveness of the SRE services on reputation escalation.
An online photo could disclose much more information beyond what is visually depicted in the photo and what its owner expects to share. In the future work, we plan to explore the potential privacy threats arising from sharing digital photos online. We will first investigate the prevalence of privacy information among digital photos. Then we introduce an attack vector not exploited before and demonstrate its surprising power in identifying a photographer with just one photo she ever took. Finally, we will build a proof-of-concept tool to alert users on potential privacy disclosure.
Bio:
Haitao Xu received his Bachelor of Science in Computer Science from Zhengzhou University, Zhengzhou, China in 2007 and Master of Engineering in Computer Science from University of Chinese Academy of Sciences, Beijing, China in 2010. He is currently pursuing Ph.D. degree in the Department of Computer Science at the College of William & Mary. His research interests lie in Web Security, Online Fraud Detection and Network Security.
Contact
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