Results 251 to 260 of about 29,077 (283)

A hybrid federated learning framework with generative AI for privacy-preserving and sustainable security in IOT-enabled smart environments. [PDF]

Sci Rep
Ramalingam V, Kumar B, Gupta SK, Alsekait DM, AbdElminaam DS.   +4 more
europepmc   +1 more source

Federated microservices architecture with blockchain for privacy-preserving and scalable healthcare analytics. [PDF]

Sci Rep
Harshith M, Ansari ZA, Fatima S, Siddiqui S, Swarna S, Reddy DRN, Mohsin SW.   +6 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Privacy preserving classification on local differential privacy in data centers

Journal of Parallel and Distributed Computing, 2020
With the rise of cloud service providers and the continuous virtualization of data centers, data center networks are also developing rapidly. As data centers become more and more complex, the demand for security increases dramatically. This paper discusses the privacy inherent in data centers.
Weibei Fan, Jing He, Mengjiao Guo
exaly   +4 more sources

Local Differential Privacy for Data Clustering

Proceedings of the 21st International Conference on Security and Cryptography
This study presents an innovative framework that utilizes Local Differential Privacy (LDP) to address the challenge of data privacy in practical applications of data clustering. Our framework is designed to prioritize the protection of individual data privacy by empowering users to proactively safeguard their information before it is shared to any ...
Bruder, Lisa, Alishahi, Mina
openaire   +2 more sources

Privacy Enhanced Matrix Factorization for Recommendation with Local Differential Privacy

IEEE Transactions on Knowledge and Data Engineering, 2018
Recommender systems are collecting and analyzing user data to provide better user experience. However, several privacy concerns have been raised when a recommender knows user's set of items or their ratings. A number of solutions have been suggested to improve privacy of legacy recommender systems, but the existing solutions in the literature can ...
Hyejin Shin, Sungwook Kim 0001, Junbum Shin, Xiaokui Xiao   +3 more
openaire   +4 more sources

Quantum Differential Privacy in the Local Model

IEEE Transactions on Information Theory
Differential privacy provides a robust framework for protecting sensitive data, while maintaining its utility for computation. In essence, a differentially private algorithm takes as input the data of multiple parties, and returns an output disclosing ...
Armando Angrisani, Elham Kashefi
openaire   +2 more sources

Local differential privacy and its applications: A comprehensive survey

Computer Standards and Interfaces
With the rapid development of low-cost consumer electronics and pervasive adoption of next generation wireless communication technologies, a tremendous amount of data has been generated from users’ smart devices and collected for research and analysis ...
Mengmeng Yang, Taolin Guo, Tianqing Zhu   +2 more
exaly   +2 more sources

Differential Privacy in the Local Setting

Proceedings of the Fourth ACM International Workshop on Security and Privacy Analytics, 2018
Differential privacy has been increasingly accepted as the de facto standard for data privacy in the research community. While many algorithms have been developed for data publishing and analysis satisfying differential privacy, there have been few deployment of such techniques.
openaire   +1 more source