Search Results for author:
Found 3 papers, 0 papers with code
Privacy Preserving Face Recognition Utilizing Differential Privacy
Biometric information delivered to untrusted third-party servers in an uncontrolled manner can be considered a significant privacy leak (i. e. uncontrolled information release) as biometrics can be correlated with sensitive data such as healthcare or financial records.
Cryptography and Security Databases
Privacy Preserving Distributed Machine Learning with Federated Learning
Distributed devices such as the Internet of Things (IoT) often produce a large amount of data, eventually resulting in big data that can be vital in uncovering hidden patterns, and other insights in numerous fields such as healthcare, banking, and policing.
Databases
Local Differential Privacy for Deep Learning
However, DL algorithms tend to leak privacy when trained on highly sensitive crowd-sourced data such as medical data.
