Explores PMKs, CMKs, BYOK, and HYOK, showing how cloud key management models affect risk, control, and regulatory compliance.

Explore post-quantum cryptography in federated learning for Model Context Protocol training. Learn about quantum vulnerabilities, security measures, and real-world applications.

Explore privacy-preserving biometric verification techniques using handwritten inputs. Learn about securing sensitive data with homomorphic encryption and zero-knowledge proofs for authentication.

A comprehensive, production-grade FHEVM Example Hub repository demonstrating how to build standalone, Hardhat-based fully homomorphic encryption examples with clean tests, automated scaffolding, and ...

Fully Homomorphic Encryption (FHE) allows data to be processed without ever being decrypted. This means a third party can run meaningful computations on encrypted information without seeing the ...

Abstract: In response to the security and privacy issues associated with sensing devices in contemporary crowd sensing systems, the paper proposes a crowd sensing networks method based on the MFHE ...

The pace of cloud adoption is relentless. Companies across every industry are racing to move their infrastructures to scalable, flexible, cloud-native environments. But as organizations go all-in on ...

Zama, a cryptography company pioneering fully homomorphic encryption (FHE) for blockchains, said it raised $57 million in a series B round co-led by Blockchange Ventures and Pantera Capital. The team ...

The spotlight on encrypted apps is also a reminder of the complex debate pitting government interests against individual liberties. Governments desire to monitor everyday communications for law ...

DataKrypto’s FHEnom for AI combines real-time homomorphic encryption with trusted execution environments to protect enterprise data and models from leakage, exposure, and tampering. AI is here – and ...