Zubair Shafiq

Associate Professor
Department of Computer Science
University of California, Davis
Office: 3043 Kemper Hall
Email | Scholar | Twitter

Research Interests

My research focuses on making the web private and secure.

Interested in working with me? Apply here

News:

• Teaching a special topics course in Spring 2024.

• Our research contributed to a FTC trade regulation rule [ANPR P214504] [Comment]

• ACM IMC 2023: Best Paper Award

• ProperData Symposium 2023

• Presented at Programmatic I/O [Slides] [Paper] [Project Website]

• Presented at Beyond the FTC: The Future of Privacy Enforcement [Watch]

• Chancellor's Fellowship

• Co-chairing Privacy Enhancing Technologies Symposium (PETS) 2024

• Filed a comment to FTC's ANPR on Commercial Surveillance and Data Security

• Co-chairing 7th Workshop on Technology and Consumer Protection (ConPro ’23) (co-located with IEEE S&P 2023)

• Co-chairing Workshop on Measurements, Attacks, and Defenses for the Web (MADWeb) (co-located with NDSS 2023)

• NSF grant on stateless tracking and browser fingerprinting

Select Recent Publications

• Google's Chrome Antitrust Paradox
  Vanderbilt Journal of Entertainment and Technology Law (JETLaw), 2024.
  

• A Scientific Approach to Tech Accountability
  Harvard Journal of Law & Technology (JoLT), 2024.
  

• Understanding Underground Incentivized Review Services
  ACM Conference on Human Factors in Computing Systems (CHI), 2024.
  

• Aragorn: A Privacy-Enhancing System for Mobile Cameras
  ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT/UbiComp), 2024.
  

• The Inventory is Dark and Full of Misinformation: Understanding Ad Inventory Pooling in the Ad-Tech Supply Chain
  IEEE Symposium on Security & Privacy (“Oakland”), 2024.
  

• Tracking, Profiling, and Ad Targeting in the Alexa Echo Smart Speaker Ecosystem
  ACM Internet Measurement Conference (IMC), 2023.
  

• Auditing YouTube's Recommendation System for Ideologically Congenial, Extreme, and Problematic Recommendations
  Proceedings of the National Academy of Sciences (PNAS), 2023.
  

• Blocking JavaScript without Breaking the Web
  Privacy Enhancing Technologies Symposium (PETS), 2023.
  

• A Utility-Preserving Obfuscation Approach for YouTube Recommendations
  Privacy Enhancing Technologies Symposium (PETS), 2023.
  

• CookieGraph: Understanding and Detecting First-Party Tracking Cookies
  ACM Conference on Computer and Communications Security (CCS), 2023.
  

• AutoFR: Automated Filter Rule Generation for Adblocking
  USENIX Security Symposium (Security), 2023.
  

• Accuracy-Privacy Trade-off in Deep Ensemble: A Membership Inference Perspective
  IEEE Symposium on Security & Privacy (“Oakland”), 2023.