What We Can Learn from AdNauseam about the Threat and Power of Data Obfuscation

Published on ● Video Link: https://www.youtube.com/watch?v=vZpu3UrGeZg



Duration: 1:24:01
1,711 views
42


Helen Nissenbaum (Cornell Tech)
Theoretically Speaking Series
https://simons.berkeley.edu/events/nissenbaum




Other Videos By Simons Institute for the Theory of Computing


2019-04-09Differentially Private Inference for Regression Coefficients
2019-04-09Analyzing Administrative Data with Privacy Protection in Place
2019-04-09Shrinkwrap: Differentially-Private Query Processing in Private Data Federations
2019-04-09Practical Difficulties in the Application of Differential Privacy for the Release of Large-Scale...
2019-04-08The Structure of Optimal Private Tests for Simple Hypotheses
2019-04-08Differentially Private Inference for Binomial Data
2019-04-08Robust Statistics and Bias Correction: Ideas for Differential Privacy and Utility
2019-04-08Differential Privacy with Elliptical Stochastic Processes
2019-04-08Finite Sample Differentially Private Confidence Intervals
2019-04-08Locally Private Bayesian Inference for Count Models
2019-04-03What We Can Learn from AdNauseam about the Threat and Power of Data Obfuscation
2019-03-22A Combinatorial Approach to Complexity Transitions in Quantum Physics
2019-03-22Christoffel-Darboux Type Identities for the Independence Polynomial
2019-03-22Counting Hypergraph Colorings in the Local Lemma Regime
2019-03-22Negative Dependence and Lorentzian Polynomials
2019-03-21Gauges, Loops, and Polynomials for Partition Functions of Graphical Models
2019-03-21Finding Eigenvalues in Exponential Size Space:...
2019-03-21Algorithmic Pirogov-Sinai Theory
2019-03-21Counting Independent Sets and Colorings on Almost Every Random Regular Bipartite Graph
2019-03-21Abstract Polymer Models and the Cluster Expansion
2019-03-20A Poly-time Deterministic Algorithm for Simply Exponential Approximation...



Tags:
Simons Institute
theoretical computer science
UC Berkeley
Helen Nissenbaum
Theoretically Speaking
Privacy