14 citations · 29 across the 6 of their papers we have counts for
3 papers · 1 filter
Privacy Leakage Avoidance with Switching Ensembles
Rauf Izmailov, Peter Lin, Chris Mesterharm +1
We consider membership inference attacks, one of the main privacy issues in machine learning. These recently developed attacks have been proven successful in determining, with conf…
Membership Model Inversion Attacks for Deep Networks
Samyadeep Basu, Rauf Izmailov, Chris Mesterharm
With the increasing adoption of AI, inherent security and privacy vulnerabilities formachine learning systems are being discovered. One such vulnerability makes itpossible for an a…
Subspace Methods That Are Resistant to a Limited Number of Features Corrupted by an Adversary
Chris Mesterharm, Rauf Izmailov, Scott Alexander +1
In this paper, we consider batch supervised learning where an adversary is allowed to corrupt instances with arbitrarily large noise. The adversary is allowed to corrupt any fe…