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Probabilistic Data Structures in Adversarial Environments
May 11 (2022) @ 2:00 pm - 3:00 pm
(Note this seminar is scheduled at 2:00 PM rather than the normal 3:00 PM slot.)
Probabilistic Data Structures (PDS) are heavily used nowadays as a means of dealing with big data, at the cost of only giving approximately correct answers to queries. Typical examples include HyperLogLog for approximate set cardinality estimation and Bloom filters for handling approximate set membership queries. In this talk I’ll focus on two basic questions:
- What can go wrong when PDS are faced with adversarially-chosen input?
- How can we protect PDS against manipulation in these adversarial environments?
Joint work with Mia Filic, Mathilde Raynal, Fernando Virdia, and Anupama Unnikrishnan.
Meeting ID: 884 3709 7322
Youtube Live Stream: https://youtu.be/PUyTUq76xVk