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Explores privacy-preserving techniques like secret sharing and homomorphic encryption for secure computations and data protection in machine learning.
Introduces Secure Multiparty Computation techniques, covering theoretical frameworks, security models, and practical applications in privacy-preserving cryptography.
Explores privacy-preserving authentication methods, zero-knowledge proofs, Schnorr's proof of identification, and their real-world applications.
Explores Privacy-Enhancing Technologies including Tor, secure computation, and homomorphic encryption.
Introduces homomorphic encryption, enabling computation on encrypted data without decryption, covering security, applications, and practical aspects.
