Abstract: Federated Learning (FL) enables distributed model training without centralizing data, but it remains vulnerable to corrupted or adversarial clients that can degrade the global model through ...

Abstract: Modular arithmetic, particularly modular reduction, is widely used in cryptographic applications such as homomorphic encryption (HE) and zero-knowledge proofs (ZKP). High-bit-width ...

“Fully Homomorphic Encryption (FHE) enables computation directly on encrypted data but incurs massive computational and memory overheads, often exceeding plaintext execution by several orders of ...

A carefully curated collection of high-quality tools, libraries, research papers, projects, and tutorials centered around Model Context Protocol (MCP) — a novel paradigm designed to enable modular, ...