Cryptographic Primitive

Cryptographic primitives are fundamental building blocks for secure systems, enabling privacy-preserving computation and data protection. Current research focuses on improving the efficiency and security of these primitives, particularly within machine learning contexts, exploring novel architectures like xMLP for faster private inference and developing techniques to mitigate side-channel attacks and enhance federated learning security through optimized cryptographic methods. These advancements are crucial for enabling secure and private applications in diverse fields, ranging from secure communication and data analysis to the development of trustworthy AI systems.