54 citations · 74 across the 7 of their papers we have counts for
8 papers
Revisiting ML Training under Fully Homomorphic Encryption: Convergence Guarantees, Differential Privacy, and Efficient Algorithms
Yvonne Zhou, Mingyu Liang, Ivan Brugere +5
We present the first theoretical convergence analysis of machine learning training under fully homomorphic encryption (FHE), combined with a differentially private (DP) training al…
Compressed Oblivious Encoding for Homomorphically Encrypted Search
Seung Geol Choi, Dana Dachman-Soled, S. Dov Gordon +2
Fully homomorphic encryption (FHE) enables a simple, attractive framework for secure search. Compared to other secure search systems, no costly setup procedure is necessary; it is…
Transparency Tools for Fairness in AI (Luskin)
Mingliang Chen, Aria Shahverdi, Sarah Anderson +5
We propose new tools for policy-makers to use when assessing and correcting fairness and bias in AI algorithms. The three tools are: - A new definition of fairness called "controll…
Database Reconstruction from Noisy Volumes: A Cache Side-Channel Attack on SQLite
Aria Shahverdi, Mahammad Shirinov, Dana Dachman-Soled
We demonstrate the feasibility of database reconstruction under a cache side-channel attack on SQLite. Specifically, we present a Flush+Reload attack on SQLite that obtains approxi…
How to 0wn NAS in Your Spare Time
Sanghyun Hong, Michael Davinroy, Yiğitcan Kaya +2
New data processing pipelines and novel network architectures increasingly drive the success of deep learning. In consequence, the industry considers top-performing architectures a…
Security Analysis of Deep Neural Networks Operating in the Presence of Cache Side-Channel Attacks
Sanghyun Hong, Michael Davinroy, Yiǧitcan Kaya +5
Recent work has introduced attacks that extract the architecture information of deep neural networks (DNN), as this knowledge enhances an adversary's capability to conduct black-bo…