Tag: Homomorphic Encryption

Researchers have introduced VFCI, a federated framework that trains causal inference models across institutions holding different features of the same ...

A new framework for privacy-preserving healthcare analytics, published in Discover Artificial Intelligence, reports measurable gains in accuracy, latency, and communication ...

A new framework called OceanWeave combines Ocean Protocol data markets, sharded compute-to-data consensus, and encrypted federated learning, reporting 3,200 TPS ...

A systematic study of 603,000 configurations shows that optimization algorithms can find Newton–Raphson starting values for homomorphic division and square ...

A 2026 Perspective argues that privacy technologies for miniaturised biosensors must be redesigned around low-power hardware, population equity and community ...

A Paillier-CKKS framework encrypted federated-learning updates and reached 94.67% average accuracy on Medical-MNIST during simulated reverse-engineering attacks.

Researchers have designed secure multiparty computation protocols that let IoT enterprises compute set intersections and unions over exact rational numbers, ...

Researchers have unveiled a collaborative encryption framework that trains deep learning models on sensitive data up to three times faster ...

Deep reinforcement learning (DRL) is rapidly becoming a cornerstone technology in various applications, ranging from autonomous systems to advanced robotics ...