There has been an increasing interest in translating artificial intelligence (AI) research into
clinically-validated applications to improve the performance, capacity, and efficacy of …

Decentralized paradigm in the field of cybersecurity and machine learning (ML) for the
emerging Internet of Things (IoT) has gained a lot of attention from the government …

As an integral part of the decentralized finance (DeFi) ecosystem, decentralized exchanges
(DEXs) with automated market maker (AMM) protocols have gained massive traction with …

With the advance of machine learning and the Internet of Things (IoT), security and privacy
have become critical concerns in mobile services and networks. Transferring data to a …

Quantum cryptography exploits principles of quantum physics for the secure processing of
information. A prominent example is secure communication, ie, the task of transmitting …

We initiate the study of private inference on Transformer-based models in the client-server
setting, where clients have private inputs and servers hold proprietary models. Our main …

Blockchains offer a decentralized, immutable and verifiable ledger that can record
transactions of digital assets, provoking a radical change in several innovative scenarios …

Federated learning has emerged as a promising approach for collaborative and privacy-
preserving learning. Participants in a federated learning process cooperatively train a model …

We consider a scenario involving computations over a massive dataset stored distributedly
across multiple workers, which is at the core of distributed learning algorithms. We propose …

Membership inference attacks seek to infer membership of individual training instances of a
model to which an adversary has black-box access through a machine learning-as-a-service …