Zubair Shafiq

The paper empirically investigates the lead marketing ecosystem, revealing a highly non-compliant system that aggressively collects, shares, and monetizes sensitive personal data through deceptive brokerage and spam practices.

The paper introduces SST-Guard, a multi-modal browser-based system that detects and blocks server-side Google Analytics (sGA) by identifying the semantic patterns of collected data rather than relying on known tracker endpoints.

This paper systematically measured web tracking across 20 popular AI chatbots, finding that a majority share both conversational content and user identity information with third parties.

The paper introduces FP-Agent, a classifier that demonstrates that while browser fingerprints are poor discriminators for AI browsing agents, behavioral fingerprints (like typing and scrolling patterns) are highly effective for distinguishing these agents from humans and from each other.