2 citations · 2 across the 6 of their papers we have counts for
3 papers · 1 filter
Beyond Labeling Oracles: What does it mean to steal ML models?
Avital Shafran, Ilia Shumailov, Murat A. Erdogdu +1
Model extraction attacks are designed to steal trained models with only query access, as is often provided through APIs that ML-as-a-Service providers offer. Machine Learning (ML)…
Membership Inference Attacks are Easier on Difficult Problems
Avital Shafran, Shmuel Peleg, Yedid Hoshen
Membership inference attacks (MIA) try to detect if data samples were used to train a neural network model, e.g. to detect copyright abuses. We show that models with higher dimensi…
Crypto-Oriented Neural Architecture Design
Avital Shafran, Gil Segev, Shmuel Peleg +1
As neural networks revolutionize many applications, significant privacy conflicts between model users and providers emerge. The cryptography community developed a variety of techni…