隐私计算与数据要素 · 全部实体（第 31 / 100 页）

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• Sources of Power in Multiparty Negotiations
  crossref Andrew Bennett 2024-10-29T14:44:11Z 置信度 0.70
• Secure multiparty variance estimation in unbalanced resource environments
  crossref Cong Hu, Zhen Yao, Jiali Sun, Cuiling Liu 等 2024-10-08T17:46:39Z 置信度 0.70
• A Framework for Privacy-Preserving Multiparty Computation with Homomorphic Encryption and Zero-Knowledge Proofs
  In digital landscape of today’s ongoing world, the imperative for enhanced security in cloud-based data processing is paramount. This paper introduces an innovative framework that seamlessly integrates Homomorphic Encryption and Zero-Knowledge Proofs (ZKPs) to…
  crossref Janak Ghansham Dhokrat, Namita Pulgam, Tabassum Maktum, Vanita Mane 2024-11-27T19:14:16Z 置信度 0.70
• Trustworthy Machine Learning using Secure Distributed Matrix Computation
  crossref Mohammad Raeini 2024-02-05T18:09:59Z 置信度 0.70
• Secure access technology for industrial internet of things
  Abstract When terminal devices attempt to access the industrial internet of things (IIoT), preventing illegal access from untrusted terminals becomes challenging. This difficulty arises because most devices adopt the commonly used traditional methods of access…
  crossref Bingquan Wang, Jin Peng, Meili Cui 2024-08-30T02:26:02Z 置信度 0.70
• Additional‐Processing‐Free Multiparty Reversible Data Hiding Over Encrypted Domain
  ABSTRACT Multiparty reversible data hiding over encrypted domain (MRDH‐ED) provides a safeguard mechanism that enables the restoration of the original cover even if some of the data hiders are potentially compromised. Existing MRDH‐ED methods are accompanied b…
  crossref Bing Chen, Ranran Yang, Bingwen Feng, Xiuye Zhan 等 2026-04-15T13:00:56Z 置信度 0.70
• Secure Computation
  crossref 2025-01-10T20:20:57Z 置信度 0.70
• SecureED: Secure Multiparty Edit Distance for Genomic Sequences
  DNA edit distance (ED) measures the minimum number of single nucleotide insertions, substitutions, or deletions required to convert a DNA sequence into another. ED has broad applications in healthcare such as sequence alignment, genome assembly, functional ann…
  crossref Jiahui Gao, Yagaagowtham Palanikumar, Dimitris Mouris, Duong Nguyen 等 2025-03-07T23:36:18Z 置信度 0.70
• Practical Zero-Knowledge PIOP for Maliciously Secure Multiparty Homomorphic Encryption
  crossref Intak Hwang, Hyeonbum Lee, Jinyeong Seo, Yongsoo Song 2025-11-22T23:32:38Z 置信度 0.70
• Secure Multi-party Computation
  crossref 2025-01-10T20:20:57Z 置信度 0.70
• Quantum secure protocols for multiparty computations
  crossref Tapaswini Mohanty, Vikas Srivastava, Sumit Kumar Debnath, Pantelimon Stănică 2025-03-20T06:56:16Z 置信度 0.70
• A Cheating Detection and Recovery Framework for Robust Multiparty Computation in the Cloud
  crossref Richard Hernandez, Kemal Akkaya, Soamar Homsi 2025-09-15T17:36:57Z 置信度 0.70
• A User-Preference Based Secure Recommender System via Multiparty and Two-Stage Processing
  crossref Abu Naim Khan, Kazi Md. Rokibul Alam, Yasuhiko Morimoto 2026-05-06T19:37:56Z 置信度 0.70
• Enhancing Payment Channel Network Routing with Multiparty Computation
  crossref Arun Shrestha, Hsiang-Jen Hong 2025-12-24T18:43:25Z 置信度 0.70
• Secure Multi-Party Computation Techniques for Blockchain-Based Fintech Platforms
  crossref Santhosh Chitraju 2025-10-29T18:26:22Z 置信度 0.70
• Secure and Parallel Determinant Computation for Large-Scale Matrices in Edge Environments    
  The advent of edge computing has enabled resource-constrained clients to delegate intensive computational tasks to distributed edge servers, especially within Internet of Things (IoT) environments. Among such tasks, Matrix Determinant Computation (MDC) remains…
  crossref Prajwal Panth 2025-12-10T19:11:21Z 置信度 0.70
• Balancing Accuracy and Privacy in Federated Queries of Clinical Data Repositories: Algorithm Development and Validation.
  Over the past decade, the emergence of several large federated clinical data networks has enabled researchers to access data on millions of patients at dozens of health care organizations. Typically, queries are broadcast to each of the sites in the network, w…
  pubmed Yu YW, Weber GM 2020 置信度 0.82
• Secure large-scale genome-wide association studies using homomorphic encryption.
  Genome-wide association studies (GWASs) seek to identify genetic variants associated with a trait, and have been a powerful approach for understanding complex diseases. A critical challenge for GWASs has been the dependence on individual-level data that typica…
  pubmed Blatt M, Gusev A, Polyakov Y, Goldwasser S 2020 置信度 0.82
• Privacy-Preserving Analysis of Distributed Biomedical Data: Designing Efficient and Secure Multiparty Computations Using Distributed Statistical Learning Theory.
  europepmc 2019 置信度 0.80
• Artificial intelligence-powered liquid biopsy in cancer: a paradigm shift in cancer detection and personalized care.
  europepmc 2026 置信度 0.80
• A Privacy-Preserved Variational-Autoencoder for DGA Identification in the Education Industry and Distance Learning.
  europepmc 2022 置信度 0.80
• Web-Based Privacy-Preserving Multicenter Medical Data Analysis Tools Via Threshold Homomorphic Encryption: Design and Development Study.
  Data sharing in multicenter medical research can improve the generalizability of research, accelerate progress, enhance collaborations among institutions, and lead to new discoveries from data pooled from multiple sources. Despite these benefits, many medical …
  pubmed Lu Y, Zhou T, Tian Y, Zhu S 等 2020 置信度 0.82
• Multi-party co-signature scheme based on SM2.
  europepmc 2023 置信度 0.80
• Reviewing Federated Machine Learning and Its Use in Diseases Prediction.
  europepmc 2023 置信度 0.80
• Expand-and-Randomize: An Algebraic Approach to Secure Computation.
  europepmc 2021 置信度 0.80
• Applications of Federated Learning in Mobile Health: Scoping Review.
  europepmc 2023 置信度 0.80
• Emerging technologies towards enhancing privacy in genomic data sharing.
  europepmc 2019 置信度 0.80
• A systematic review of homomorphic encryption and its contributions in healthcare industry.
  Abstract Cloud computing and cloud storage have contributed to a big shift in data processing and its use. Availability and accessibility of resources with the reduction of substantial work is one of the main reasons for the cloud revolution. With this cloud c…
  pubmed Munjal K, Bhatia R, Kundan Munjal, Rekha Bhatia 2022 置信度 0.82
• Virtual medicine: medical AI in human health and diseases.
  europepmc 2026 置信度 0.80
• Computational paradigms for antimicrobial resistance prediction: integrating multi-omics, structural modeling, and foundation artificial intelligence systems.
  europepmc 2026 置信度 0.80
• Privacy-Preserving Methods for Feature Engineering Using Blockchain: Review, Evaluation, and Proof of Concept.
  europepmc 2019 置信度 0.80
• A Survey of Machine and Deep Learning Methods for Privacy Protection in the Internet of Things.
  europepmc 2023 置信度 0.80
• An Overview of Current Solutions for Privacy in the Internet of Things.
  europepmc 2022 置信度 0.80
• Privacy-Oriented Technique for COVID-19 Contact Tracing (PROTECT) Using Homomorphic Encryption: Design and Development Study.
  Various techniques are used to support contact tracing, which has been shown to be highly effective against the COVID-19 pandemic. To apply the technology, either quarantine authorities should provide the location history of patients with COVID-19, or all user…
  pubmed An Y, Lee S, Jung S, Park H 等 2021 置信度 0.82
• Centralized Threshold Key Generation Protocol Based on Shamir Secret Sharing and HMAC Authentication.
  europepmc 2022 置信度 0.80
• A Survey on Secure Computation Based on Homomorphic Encryption in Vehicular Ad Hoc Networks.
  In vehicular ad hoc networks (VANETs), the security and privacy of vehicle data are core issues. In order to analyze vehicle data, they need to be computed. Encryption is a common method to guarantee the security of vehicle data in the process of data dissemin…
  pubmed Sun X, Yu FR, Zhang P, Xie W 等 2020 置信度 0.82
• Quantum Diffie-Hellman Extended to Dynamic Quantum Group Key Agreement for e-Healthcare Multi-Agent Systems in Smart Cities.
  europepmc 2020 置信度 0.80
• Ten Topics to Get Started in Medical Informatics Research.
  europepmc 2023 置信度 0.80
• SFedChain: blockchain-based federated learning scheme for secure data sharing in distributed energy storage networks.
  europepmc 2022 置信度 0.80
• DLT Based Authentication Framework for Industrial IoT Devices.
  europepmc 2020 置信度 0.80
• Machine Learning for Healthcare Wearable Devices: The Big Picture.
  europepmc 2022 置信度 0.80
• Sharing Data With Shared Benefits: Artificial Intelligence Perspective.
  europepmc 2023 置信度 0.80
• Internet of Nano-Things (IoNT): A Comprehensive Review from Architecture to Security and Privacy Challenges.
  europepmc 2023 置信度 0.80
• A Novel Privacy Preserving Scheme for Smart Grid-Based Home Area Networks.
  Despite the benefits of smart grids, concerns about security and privacy arise when a large number of heterogeneous devices communicate via a public network. A novel privacy-preserving method for smart grid-based home area networks (HAN) is proposed in this re…
  pubmed Ali W, Din IU, Almogren A, Kim BS 2022 置信度 0.82
• Secure Logistic Regression Based on Homomorphic Encryption: Design and Evaluation.
  Learning a model without accessing raw data has been an intriguing idea to security and machine learning researchers for years. In an ideal setting, we want to encrypt sensitive data to store them on a commercial cloud and run certain analyses without ever dec…
  pubmed Kim M, Song Y, Wang S, Xia Y 等 2018 置信度 0.82
• Literature analysis of artificial intelligence in biomedicine.
  europepmc 2022 置信度 0.80
• Federated Learning in Edge Computing: A Systematic Survey.
  europepmc 2022 置信度 0.80
• Big Data Health Care Platform With Multisource Heterogeneous Data Integration and Massive High-Dimensional Data Governance for Large Hospitals: Design, Development, and Application.
  europepmc 2022 置信度 0.80
• Edge Machine Learning for AI-Enabled IoT Devices: A Review.
  europepmc 2020 置信度 0.80
• Protecting genomic data analytics in the cloud: state of the art and opportunities.
  europepmc 2016 置信度 0.80
• DiLizium: A Two-Party Lattice-Based Signature Scheme.
  europepmc 2021 置信度 0.80
• Secure and Efficient Regression Analysis Using a Hybrid Cryptographic Framework: Development and Evaluation.
  Machine learning is an effective data-driven tool that is being widely used to extract valuable patterns and insights from data. Specifically, predictive machine learning models are very important in health care for clinical data analysis. The machine learning…
  pubmed Sadat MN, Jiang X, Aziz MMA, Wang S 等 2018 置信度 0.82
• SCOTCH: Secure Counting Of encrypTed genomiC data using a Hybrid approach.
  europepmc 2017 置信度 0.80
• Data Anonymization for Pervasive Health Care: Systematic Literature Mapping Study.
  europepmc 2021 置信度 0.80
• Efficacy of federated learning on genomic data: a study on the UK Biobank and the 1000 Genomes Project.
  europepmc 2024 置信度 0.80
• A Private Quantum Bit String Commitment.
  europepmc 2020 置信度 0.80
• iDASH secure genome analysis competition 2018: blockchain genomic data access logging, homomorphic encryption on GWAS, and DNA segment searching.
  pubmed Kuo TT, Jiang X, Tang H, Wang X 等 2020 置信度 0.82
• Implementing Vertical Federated Learning Using Autoencoders: Practical Application, Generalizability, and Utility Study.
  europepmc 2021 置信度 0.80
• Artificial Intelligence in Adult Cardiovascular Medicine and Surgery: Real-World Deployments and Outcomes.
  europepmc 2026 置信度 0.80
• Privacy of Study Participants in Open-access Health and Demographic Surveillance System Data: Requirements Analysis for Data Anonymization.
  europepmc 2022 置信度 0.80
• Bridging the European Data Sharing Divide in Genomic Science.
  europepmc 2022 置信度 0.80
• SVBE: searchable and verifiable blockchain-based electronic medical records system.
  europepmc 2022 置信度 0.80
• Federated Learning on Clinical Benchmark Data: Performance Assessment.
  europepmc 2020 置信度 0.80
• Re-engineering a Clinical Trial Management System Using Blockchain Technology: System Design, Development, and Case Studies.
  europepmc 2022 置信度 0.80
• Differential privacy for public health data: An innovative tool to optimize information sharing while protecting data confidentiality.
  europepmc 2021 置信度 0.80
• Integrating artificial intelligence into small molecule development for precision cancer immunomodulation therapy.
  europepmc 2025 置信度 0.80
• Collective privacy recovery: Data-sharing coordination via decentralized artificial intelligence.
  europepmc 2024 置信度 0.80
• Swarm: A federated cloud framework for large-scale variant analysis.
  europepmc 2021 置信度 0.80
• Distributed Key Management to Secure IoT Wireless Sensor Networks in Smart-Agro.
  europepmc 2020 置信度 0.80
• Blockchain and K-Means Algorithm for Edge AI Computing.
  europepmc 2022 置信度 0.80
• PREMIX: PRivacy-preserving EstiMation of Individual admiXture.
  europepmc 2016 置信度 0.80
• Privacy-preserving storage of sequenced genomic data.
  europepmc 2021 置信度 0.80
• Challenges in AI-driven Biomedical Multimodal Data Fusion and Analysis.
  europepmc 2025 置信度 0.80
• COVID-19 detection using federated machine learning.
  europepmc 2021 置信度 0.80
• Fold-stratified cross-validation for unbiased and privacy-preserving federated learning.
  europepmc 2020 置信度 0.80
• Digital immune twins and ai-integrated multi-omic biomarkers: Redefining personalized immunotherapy in non-small cell lung cancer.
  europepmc 2026 置信度 0.80
• Blockchain and artificial intelligence technology in e-Health.
  europepmc 2021 置信度 0.80
• Next-Generation Capabilities in Trusted Research Environments: Interview Study.
  europepmc 2022 置信度 0.80
• Systematic Review of Privacy-Preserving Distributed Machine Learning From Federated Databases in Health Care.
  europepmc 2020 置信度 0.80
• The Intersection of Machine Learning and Wireless Sensor Network Security for Cyber-Attack Detection: A Detailed Analysis.
  europepmc 2024 置信度 0.80
• Mini Review: Clinical Routine Microbiology in the Era of Automation and Digital Health.
  europepmc 2020 置信度 0.80
• A Privacy-Preserving Distributed Analytics Platform for Health Care Data.
  europepmc 2022 置信度 0.80
• Is privacy <i>privacy</i>?
  europepmc 2018 置信度 0.80
• Privacy-Preserving Patient Similarity Learning in a Federated Environment: Development and Analysis.
  There is an urgent need for the development of global analytic frameworks that can perform analyses in a privacy-preserving federated environment across multiple institutions without privacy leakage. A few studies on the topic of federated medical analysis hav…
  pubmed Lee J, Sun J, Wang F, Wang S 等 2018 置信度 0.82
• Exploring the Relationship Between Privacy and Utility in Mobile Health: Algorithm Development and Validation via Simulations of Federated Learning, Differential Privacy, and External Attacks.
  europepmc 2023 置信度 0.80
• Decision Processes in Multiparty Negotiations
  crossref Andrew Bennett 2024-10-29T14:44:11Z 置信度 0.70
• Enhancing data authentication in software-defined networking (SDN) using multiparty computation
  crossref Fatma Hendaoui, Hamdi Eltaief, Habib Youssef 2024-06-15T14:01:25Z 置信度 0.70
• Multiple Priorities in Multiparty Negotiations
  crossref Andrew Bennett 2024-10-29T14:44:11Z 置信度 0.70
• Decision Rules in Multiparty Negotiations
  crossref Andrew Bennett 2024-10-29T14:44:11Z 置信度 0.70
• An efficient secure multiparty quantum computation protocol
  crossref LIN Song, WANG Ning, LIU Xiao-Fen 2023-02-15T06:24:42Z 置信度 0.70
• FaultyGarble: Fault Attack on Secure Multiparty Neural Network Inference
  crossref Mohammad Hashemi, Dev Mehta, Kyle Mitard, Shahin Tajik 等 2024-11-04T13:33:30Z 置信度 0.70
• Coalitions in Multiparty Negotiations
  crossref Andrew Bennett 2024-10-29T14:44:11Z 置信度 0.70
• Straw Votes in Multiparty Negotiations
  crossref Andrew Bennett 2024-10-29T14:44:11Z 置信度 0.70
• GNN-RMNet: Leveraging graph neural networks and GPS analytics for driver behavior and route optimization in logistics.
  europepmc 2025 置信度 0.80
• Truly privacy-preserving federated analytics for precision medicine with multiparty homomorphic encryption.
  Using real-world evidence in biomedical research, an indispensable complement to clinical trials, requires access to large quantities of patient data that are typically held separately by multiple healthcare institutions. We propose FAMHE, a novel federated an…
  pubmed Froelicher D, Troncoso-Pastoriza JR, Raisaro JL, Cuendet MA 等 2021 置信度 0.82
• Privacy-Preserving Verification of ML Preprocessing via Model Behavior Indicators.
  europepmc 2025 置信度 0.80
• Selecting Privacy-Enhancing Technologies for Managing Health Data Use.
  europepmc 2022 置信度 0.80
• Trust and class aware service discovery with dual control in the social Internet of Things.
  europepmc 2026 置信度 0.80
• Artificial intelligence in pancreatitis: A narrative review on advancing precision diagnosis, prognosis, and therapeutic strategies.
  europepmc 2025 置信度 0.80
• The Limitations of Artificial Intelligence in Head and Neck Oncology.
  europepmc 2025 置信度 0.80