Results 11 to 20 of about 104,369 (254)
Comprehensive location privacy enhanced model
iScienceSummary: With the increasing popularity of location-based services (LBSs), safeguarding location privacy has become critically important. Traditional methods often struggle to balance the intensity of privacy protection with service quality.
Haohua Qing +2 more
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Privacy-Enhanced Personalization [PDF]
Communications of the ACM, 2007 Multi-pronged strategies are needed to reconcile the tension between personalization and privacy.
Alfred Kobsa +2 more
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Privacy-enhanced federated learning scheme based on generative adversarial networks
网络与信息安全学报, 2023 Federated learning, a distributed machine learning paradigm, has gained a lot of attention due to its inherent privacy protection capability and heterogeneous collaboration.However, recent studies have revealed a potential privacy risk known as “gradient
Feng YU, Qingxin LIN, Hui LIN, Xiaoding WANG
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Preserving Privacy in Arabic Judgments: AI-Powered Anonymization for Enhanced Legal Data Privacy
IEEE Access, 2023 Jurisprudence involves studying, interpreting, and applying the law to comprehend its societal impact. Judges annually review cases to ensure accurate law application, which raises privacy concerns when accessing files from other courts.
Taoufiq El Moussaoui +2 more
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Privacy-Enhanced AKMA for Multi-Access Edge Computing Mobility
Computers, 2022 Multi-access edge computing (MEC) is an emerging technology of 5G that brings cloud computing benefits closer to the user. The current specifications of MEC describe the connectivity of mobile users and the MEC host, but they have issues with application-
Gizem Akman +3 more
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FREDY: Federated Resilience Enhanced with Differential Privacy
Future Internet, 2023 Federated Learning is identified as a reliable technique for distributed training of ML models. Specifically, a set of dispersed nodes may collaborate through a federation in producing a jointly trained ML model without disclosing their data to each ...
Zacharias Anastasakis +6 more
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网络与信息安全学报With the development of cloud computing and internet of things technology, verifiable computing has been widely used as a new computing technology. While verifiable computing brings convenience to users, there are also security challenges: data privacy ...
Tianpeng ZHANG, Zhiyu REN, Xuehui DU, Haichao WANG
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Privacy-Preserving Federated Singular Value Decomposition
Applied Sciences, 2023 Singular value decomposition (SVD) is a fundamental technique widely used in various applications, such as recommendation systems and principal component analyses.
Bowen Liu, Balázs Pejó, Qiang Tang
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An Enhanced Differential Privacy Data Release Algorithm [PDF]
Jisuanji gongcheng, 2017 In order to improve the classification accuracy of released data under the same privacy preserving strength,on the basis of DiffGen algorithm,an enhanced differential privacy data release algorithm named as GiniDiff is proposed.This algorithm completely ...
SUN Kui,ZHANG Zhiyong,ZHAO Changwei
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Privacy-enhanced Federated Learning Algorithm Against Inference Attack [PDF]
Jisuanji kexue, 2023 In federated learning,each distributed client does not need to transmit local training data,the central server jointly trains the global model by gradient collection,it has good performance and privacy protection advantages.However,it has been ...
ZHAO Yuhao, CHEN Siguang, SU Jian
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