Explores machine learning fundamentals and privacy risks, focusing on privacy attacks and collaborative machine learning.
Explores homomorphic encryption, enabling computations on encrypted data without decryption, with practical applications in secure medical clouds.
Explores the historical development and legal aspects of data protection laws, international instruments, challenges of online tracking, legal bases for processing personal data, and privacy regulations.
Covers the historical development and key concepts of homomorphic encryption, focusing on the Paillier cryptosystem and the BGV cryptosystem.
Explores privacy-preserving authentication methods, zero-knowledge proofs, Schnorr's proof of identification, and their real-world applications.
Explores the sensitivity of location data, inference of points of interest, and techniques for protecting location privacy.
Covers the measurement of privacy in location data, defense mechanisms, and challenges in protecting location privacy.
Explores the significance of anonymous communications in safeguarding privacy and security, covering challenges, applications, system design, and quantifying anonymity levels.
Delves into anonymous communication systems, discussing Herbivore protocol, statistical disclosure attacks, Crowds system, and anonymity analysis.
