219 citations · 263 across the 7 of their papers we have counts for
6 papers · 1 filter
MemFHE: End-to-End Computing with Fully Homomorphic Encryption in Memory
Saransh Gupta, Rosario Cammarota, Tajana Rosing
The increasing amount of data and the growing complexity of problems has resulted in an ever-growing reliance on cloud computing. However, many applications, most notably in health…
Guarding Machine Learning Hardware Against Physical Side-Channel Attacks
Anuj Dubey, Rosario Cammarota, Vikram Suresh +1
Machine learning (ML) models can be trade secrets due to their development cost. Hence, they need protection against malicious forms of reverse engineering (e.g., in IP piracy). Wi…
Trustworthy AI Inference Systems: An Industry Research View
Rosario Cammarota, Matthias Schunter, Anand Rajan +26
In this work, we provide an industry research view for approaching the design, deployment, and operation of trustworthy Artificial Intelligence (AI) inference systems. Such systems…
BoMaNet: Boolean Masking of an Entire Neural Network
Anuj Dubey, Rosario Cammarota, Aydin Aysu
Recent work on stealing machine learning (ML) models from inference engines with physical side-channel attacks warrant an urgent need for effective side-channel defenses. This work…
MaskedNet: The First Hardware Inference Engine Aiming Power Side-Channel Protection
Anuj Dubey, Rosario Cammarota, Aydin Aysu
Differential Power Analysis (DPA) has been an active area of research for the past two decades to study the attacks for extracting secret information from cryptographic implementat…
nGraph-HE2: A High-Throughput Framework for Neural Network Inference on Encrypted Data
Fabian Boemer, Anamaria Costache, Rosario Cammarota +1
In previous work, Boemer et al. introduced nGraph-HE, an extension to the Intel nGraph deep learning (DL) compiler, that enables data scientists to deploy models with popular frame…