Results 21 to 30 of about 41,188 (261)
CoRR, 2018 Ensuring differential privacy of models learned from sensitive user data is an important goal that has been studied extensively in recent years. It is now known that for some basic learning problems, especially those involving high-dimensional data, producing an accurate private model requires much more data than learning without privacy.
Cynthia Dwork, Vitaly Feldman
openaire +3 more sources
Privacy Preserving Clustering [PDF]
, 2005 The freedom and transparency of information flow on the Internet has heightened concerns of privacy. Given a set of data items, clustering algorithms group similar items together. Clustering has many applications, such as customerbehavior analysis, targeted marketing, forensics, and bioinformatics. In this paper, we present the design and analysis of a
Somesh Jha +2 more
openaire +1 more source
PEIGEN – a Platform for Evaluation, Implementation, and Generation of S-boxes
IACR Transactions on Symmetric Cryptology, 2019 In this paper, a platform named PEIGEN is presented to evaluate security, find efficient software/hardware implementations, and generate cryptographic S-boxes.
Zhenzhen Bao +3 more
doaj +1 more source
Privacy Preserving Average Consensus [PDF]
IEEE Transactions on Automatic Control, 2014 Average consensus is a widely used algorithm for distributed computing and control, where all the agents in the network constantly communicate and update their states in order to achieve an agreement. This approach could result in an undesirable disclosure of information on the initial state of agent i to the other agents.
Yilin Mo, Richard M. Murray
openaire +3 more sources
Privacy-preserving machine learning based on secure three-party computations
Безопасность информационных технологий, 2022 The paper is devoted to the analysis of privacy-preserving machine learning systems based on the concept of secure three-party computations. After general information about the purposes of secure multi-party computations and privacy-preserving machine ...
Sergey V. Zapechnikov
doaj +1 more source
Privacy Preserving Data Mining [PDF]
Journal of Cryptology, 2000 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yehuda Lindell, Benny Pinkas
openaire +2 more sources
Privacy Computing: Concept, Computing Framework, and Future Development Trends
Engineering, 2019 With the rapid development of information technology and the continuous evolution of personalized services, huge amounts of data are accumulated by large internet companies in the process of serving users. Moreover, dynamic data interactions increase the
Fenghua Li, Hui Li, Ben Niu, Jinjun Chen
doaj +1 more source
Lead federated neuromorphic learning for wireless edge artificial intelligence
Nature Communications, 2022 Designing energy-efficient computing solution for the implementation of AI algorithms in edge devices remains a challenge. Yang et al. proposes a decentralized brain-inspired computing method enabling multiple edge devices to collaboratively train a ...
Helin Yang +6 more
doaj +1 more source
PP-GWAS: Privacy Preserving Multi-Site Genome-wide Association Studies
Nature CommunicationsGenome-wide association studies help uncover genetic influences on complex traits and diseases. Importantly, multi-site data collaborations enhance the statistical power of these studies but pose challenges due to the sensitivity of genomic data ...
Arjhun Swaminathan +4 more
doaj +1 more source
Accountable Privacy-Preserving Mechanism for Cloud Computing Based on Identity-Based Encryption
IEEE Access, 2018 Considering the openness and cross-domains of cloud computing, the traditional privacy-preserving technology cannot be applied in cloud computing efficiently.
Hongbing Cheng +3 more
doaj +1 more source