96 citations · 130 across the 7 of their papers we have counts for
5 papers · 1 filter
Investigating Privacy Attacks in the Gray-Box Setting to Enhance Collaborative Learning Schemes
Federico Mazzone, Ahmad Al Badawi, Yuriy Polyakov +3
The notion that collaborative machine learning can ensure privacy by just withholding the raw data is widely acknowledged to be flawed. Over the past seven years, the literature ha…
TREBUCHET: Fully Homomorphic Encryption Accelerator for Deep Computation
David Bruce Cousins, Yuriy Polyakov, Ahmad Al Badawi +21
Secure computation is of critical importance to not only the DoD, but across financial institutions, healthcare, and anywhere personally identifiable information (PII) is accessed.…
PrivFT: Private and Fast Text Classification with Homomorphic Encryption
Ahmad Al Badawi, Luong Hoang, Chan Fook Mun +2
The need for privacy-preserving analytics is higher than ever due to the severity of privacy risks and to comply with new privacy regulations leading to an amplified interest in pr…
CaRENets: Compact and Resource-Efficient CNN for Homomorphic Inference on Encrypted Medical Images
Jin Chao, Ahmad Al Badawi, Balagopal Unnikrishnan +9
Convolutional neural networks (CNNs) have enabled significant performance leaps in medical image classification tasks. However, translating neural network models for clinical appli…
Towards the AlexNet Moment for Homomorphic Encryption: HCNN, theFirst Homomorphic CNN on Encrypted Data with GPUs
Ahmad Al Badawi, Jin Chao, Jie Lin +6
Deep Learning as a Service (DLaaS) stands as a promising solution for cloud-based inference applications. In this setting, the cloud has a pre-learned model whereas the user has sa…