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Explore a conference presentation that investigates privacy vulnerabilities in group messaging platforms where chatbots can access sensitive user information beyond their intended functions. Learn how researchers from National Taiwan University, HRL Laboratories, and Academia Sinica analyzed conversation datasets to reveal that chatbots frequently access more messages than necessary and can recognize users across different groups with a 3.6% probability. Discover the limitations of current group messaging protocols that fail to combine end-to-end encryption with effective chatbot access controls. Examine SnoopGuard, a novel secure group messaging protocol that addresses these privacy concerns through selective message access and sender anonymity features. Understand the technical implementation details, including the protocol's O(log n + m) message-sending complexity and prototype performance results showing 10-millisecond message delivery times for groups of 50 users and 10 chatbots when integrated with Message Layer Security (MLS).
