Ad-Mageddon: The Next Frontier in Online Privacy

Prof. Zubair Shafiq, University of California, Davis

Short Bio:
Zubair Shafiq is an associate professor of computer science at University of California, Davis. Prior to joining UC Davis, he was on faculty at the University of Iowa. He received his PhD from Michigan State University in 2014. His research focuses on making the Internet more private, secure, and efficient using network measurement and machine learning techniques. 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), IEEE ICNP Best Paper Award (2012), Fitch-Beach Outstanding Graduate Research Award (2013), and the Dean’s Plaque of Excellence for undergraduate research (2007, 2008).

Date:July 16, 2020
Time: 4:00 PM IST


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.