- When: Thursday, February 13, 2020 from 02:00 PM to 03:00 PM
- Speakers: Zubair Shafiq
- Location: Engineering Building 4201
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While online advertising supports the "free" web, it relies on a complex and opaque tracking ecosystem that surveils users across the web. Hundreds of millions of users rely on ad-blocking and anti-tracking tools to counter the negative externalities of online advertising and tracking. Perhaps unsurprisingly, advertisers are increasingly retaliating against the users of such tools -- prompting an arms race.
In this talk, I will first discuss the pain points of the state-of-the-art ad-blocking and anti-tracking tools. I will then describe our recent work on building effective and robust countermeasures against online advertising and tracking using machine learning techniques. I will highlight the unique challenges and opportunities in deploying ad-blocking and anti-tracking tools in web browsers as well as mobile and IoT systems. I will conclude with a discussion of my future research vision for a privacy-respecting web.
Zubair Shafiq is an assistant professor of computer science at the University of Iowa. Prior to this, he received his Ph.D. from Michigan State University in 2014. His research focuses on building privacy-enhancing tools to counter online tracking and surveillance. More broadly, his work takes a data-driven approach to addressing emerging online privacy and security threats. He is a recipient of the NSF CAREER Award (2018), Andreas Pfitzmann PETS Best Student Paper Award (2018), ACM IMC Best Paper Award (2017), NSF CRII Award (2015), Fitch-Beach Outstanding Graduate Research Award (2013), IEEE ICNP Best Paper Award (2012), and the Dean's Plaque of Excellence for undergraduate research (2007, 2008). More information at https://cs.uiowa.edu/~mshafiq