隐私计算与数据要素 · 全部实体（第 27 / 100 页）

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• Blockchain-Based Secure Multi-Party Computation (SMPC) Protocols
  This paper proposes a novel approach to Secure Multi-Party Computation (SMPC) utilizing blockchain technology. Existing SMPC protocols often rely on trusted third parties, introducing single points of failure and potential vulnerabilities. Our framework addres…
  datacite Zhang, Jincheng 2026 置信度 0.66
• Blockchain-Based Secure Multi-Party Computation (SMPC) Protocols
  This paper proposes a novel approach to Secure Multi-Party Computation (SMPC) utilizing blockchain technology. Existing SMPC protocols often rely on trusted third parties, introducing single points of failure and potential vulnerabilities. Our framework addres…
  datacite Zhang, Jincheng 2026 置信度 0.66
• Homomorphic Encryption-Based Distributed Database Querying
  This paper proposes a novel system for distributed database querying that leverages the power of homomorphic encryption (HE) and differential privacy (DP) to provide secure and privacy-preserving query capabilities. The core idea is to perform all query operat…
  datacite Zhang, Jincheng 2026 置信度 0.66
• Homomorphic Encryption-Based Distributed Database Querying
  This paper proposes a novel system for distributed database querying that leverages the power of homomorphic encryption (HE) and differential privacy (DP) to provide secure and privacy-preserving query capabilities. The core idea is to perform all query operat…
  datacite Zhang, Jincheng 2026 置信度 0.66
• Decentralized Machine Learning via Secure Multi-Party Computation and Homomorphic Encryption
  This paper proposes a novel framework for decentralized machine learning (DML) that prioritizes data privacy and security. The core of the approach lies in the synergistic utilization of Secure Multi-Party Computation (SMPC) and Homomorphic Encryption (HE). Tr…
  datacite Zhang, Jincheng 2026 置信度 0.66
• Decentralized Machine Learning via Secure Multi-Party Computation and Homomorphic Encryption
  This paper proposes a novel framework for decentralized machine learning (DML) that prioritizes data privacy and security. The core of the approach lies in the synergistic utilization of Secure Multi-Party Computation (SMPC) and Homomorphic Encryption (HE). Tr…
  datacite Zhang, Jincheng 2026 置信度 0.66
• HPAO Artifact
  Fully Homomorphic Encryption (FHE) enables computation on encrypted data without decryption, but its overhead relative to plaintext execution remains a major barrier to practical deployment. Existing FHE software stacks expose only coarse-grained cryptographic…
  datacite Sui, Tianxiang 2026 置信度 0.66 FHECKKSFHE Compiler
• HPAO Artifact
  Fully Homomorphic Encryption (FHE) enables computation on encrypted data without decryption, but its overhead relative to plaintext execution remains a major barrier to practical deployment. Existing FHE software stacks expose only coarse-grained cryptographic…
  datacite Sui, Tianxiang 2026 置信度 0.66 FHECKKSFHE Compiler
• Based on Blockchain Distributed Secure Computation Engine
  This paper proposes a novel distributed secure computation engine based on blockchain technology. The core claim is to leverage blockchain's inherent trust and traceability mechanisms to secure computation, guaranteeing the integrity and security of the result…
  datacite Zhang, Jincheng 2026 置信度 0.66
• Based on Blockchain Distributed Secure Computation Engine
  This paper proposes a novel distributed secure computation engine based on blockchain technology. The core claim is to leverage blockchain's inherent trust and traceability mechanisms to secure computation, guaranteeing the integrity and security of the result…
  datacite Zhang, Jincheng 2026 置信度 0.66
• EncFormer: Secure and Efficient Transformer Inference over Encrypted Data
  Official self-contained implementation of EncFormer. The archive contains the GPU CKKS implementation, CKKS--MPC conversion, BPMax, MBNorm, BOLT GELU, real two-party EzPC/SCI execution, native dependency source, the BERT-base SST-2 checkpoint, local evaluation…
  datacite Zhu, Yufan, Jin, Chao, Aung, Khin Mi Mi, Xiao, Xiaokui 2026 置信度 0.66 EncFormerhomomorphic encryptionsecure multi-party computationprivate Transformer inferenceCKKS
• EncFormer: Secure and Efficient Transformer Inference over Encrypted Data
  Official self-contained implementation of EncFormer. The archive contains the GPU CKKS implementation, CKKS--MPC conversion, BPMax, MBNorm, BOLT GELU, real two-party EzPC/SCI execution, native dependency source, the BERT-base SST-2 checkpoint, local evaluation…
  datacite Zhu, Yufan, Jin, Chao, Aung, Khin Mi Mi, Xiao, Xiaokui 2026 置信度 0.66 EncFormerhomomorphic encryptionsecure multi-party computationprivate Transformer inferenceCKKS
• The Architecture of Readiness: Synthesising Ancient Wisdom, Cryptography, and Artificial Intelligence
  This article presents a philosophy of professional readiness, arguing that periods of economic downturn and career stagnation should be strategically repurposed as intensive 'training periods'. This proactive paradigm advocates for shifting focus away from unc…
  datacite Majumdar, Partha 2026 置信度 0.66 Philosophy
• The Architecture of Readiness: Synthesising Ancient Wisdom, Cryptography, and Artificial Intelligence
  This article presents a philosophy of professional readiness, arguing that periods of economic downturn and career stagnation should be strategically repurposed as intensive 'training periods'. This proactive paradigm advocates for shifting focus away from unc…
  datacite Majumdar, Partha 2026 置信度 0.66 Philosophy
• Homomorphic Encryption for Secure Data Processing in Edge Computing
  datacite Safa Mohamed, Ali Majad 2026 置信度 0.66
• Homomorphic Encryption for Secure Data Processing in Edge Computing
  datacite Safa Mohamed, Ali Majad 2026 置信度 0.66
• Privacy Rights in the Digital Age: Challenges, Opportunities, and Future Horizons
  Privacy, as one of the most fundamental human rights, has undergone profound paradigm shifts in the transition from the industrial age to the digital age. While the traditional concept of privacy was based on the "right to be let alone" and the Inviolability o…
  datacite Taherimanesh, Mehdi 2025 置信度 0.66 Digital Privacy, Data Rights, Artificial Intelligence, Surveillance Capitalism, Cryptography, Information Technology Law
• Privacy Rights in the Digital Age: Challenges, Opportunities, and Future Horizons
  Privacy, as one of the most fundamental human rights, has undergone profound paradigm shifts in the transition from the industrial age to the digital age. While the traditional concept of privacy was based on the "right to be let alone" and the Inviolability o…
  datacite Taherimanesh, Mehdi 2025 置信度 0.66 Digital Privacy, Data Rights, Artificial Intelligence, Surveillance Capitalism, Cryptography, Information Technology Law
• ATLAS: Automated Approximation of Transformers for Efficient Homomorphic Inference in One Hour
  Fully homomorphic encryption (FHE) lets a server run inference on encrypted data with strong privacy guarantees, but running a Transformer under FHE is expensive. Its non-linear operations, such as softmax, normalization, and activation, must be replaced with …
  datacite Xie, Jianhang, Tan, Sicheng, Boddeti, Vishnu Naresh, Lu, Zhichao 2026 置信度 0.66 Cryptography and Security (cs.CR)Artificial Intelligence (cs.AI)Machine Learning (cs.LG)FOS: Computer and information sciences
• A Collusion-Resistance Privacy-Preserving Smart Metering Protocol for Operational Utility
  Modern smart grids rely on advanced metering infrastructure (AMI) to collect fine-grained consumption readings for operational services such as grid monitoring, load forecasting, and demand--supply balancing. However, these high-frequency readings can reveal s…
  datacite Zaredar, Farid, Amini, Morteza 2025 置信度 0.66 Cryptography and Security (cs.CR)FOS: Computer and information sciences
• Homomorphic encryption & CNN
  datacite Guobin, Zhang 2026 置信度 0.66
• Homomorphic encryption & CNN
  datacite Guobin, Zhang 2026 置信度 0.66
• THEMIS: Bringing Verifiability to RNS-CKKS Homomorphic Encryption
  datacite Anonymous, Anonymous 2026 置信度 0.66
• THEMIS: Bringing Verifiability to RNS-CKKS Homomorphic Encryption
  datacite Anonymous, Anonymous 2026 置信度 0.66
• FHE-Lab: A Modular Framework for Customizable Fully Homomorphic Encryption Pipelines
  FHE-Lab is a lightweight FHE library designed to enable highly customizable pipeline configurations, allowing researchers to experiment with implementation choices, evaluate optimizations and reliability, analyze intermediate computation stages, and study trad…
  datacite Chan, Vattana, Mazzanti, Matias 2026 置信度 0.66
• FHE-Lab: A Modular Framework for Customizable Fully Homomorphic Encryption Pipelines
  FHE-Lab is a lightweight FHE library designed to enable highly customizable pipeline configurations, allowing researchers to experiment with implementation choices, evaluate optimizations and reliability, analyze intermediate computation stages, and study trad…
  datacite Chan, Vattana, Mazzanti, Matias 2026 置信度 0.66
• Online Fingerprint Authentication Scheme over Outsourced Data
  With the rifeness of mobile plans and the growth of biometric technology, biometric credentials, which can realize separate verification trusts on individual life or social physiognomies, has involved widely substantial interest. Though, confidentiality subjec…
  datacite B, Tilak, N., Vaishnavi 2025 置信度 0.66 Biometric Authentication; Privacy-Preserving Verification; Online Fingerprint Matching; Outsourced Data; Homomorphic Encryption; Secure Euclidean Distance Calculation; Fingerprint Data Protection; Cloud Security; e-Finga Scheme; Data Confidentiality
• Online Fingerprint Authentication Scheme over Outsourced Data
  With the rifeness of mobile plans and the growth of biometric technology, biometric credentials, which can realize separate verification trusts on individual life or social physiognomies, has involved widely substantial interest. Though, confidentiality subjec…
  datacite B, Tilak, N., Vaishnavi 2025 置信度 0.66 Biometric Authentication; Privacy-Preserving Verification; Online Fingerprint Matching; Outsourced Data; Homomorphic Encryption; Secure Euclidean Distance Calculation; Fingerprint Data Protection; Cloud Security; e-Finga Scheme; Data Confidentiality
• Federated Learning: Advancing Privacy-Preserving Machine Learning at Scale
  Federated Learning emerges as a transformative paradigm in machine learning, revolutionizing data privacy and distributed computing across multiple sectors. This comprehensive exploration details the evolution of federated learning from its foundational concep…
  datacite Gupta, Shreya 2025 置信度 0.66 Federated Learning; Privacy Preservation; Distributed Computing; Edge Computing; Machine Learning Integration
• Federated Learning: Advancing Privacy-Preserving Machine Learning at Scale
  Federated Learning emerges as a transformative paradigm in machine learning, revolutionizing data privacy and distributed computing across multiple sectors. This comprehensive exploration details the evolution of federated learning from its foundational concep…
  datacite Gupta, Shreya 2025 置信度 0.66 Federated Learning; Privacy Preservation; Distributed Computing; Edge Computing; Machine Learning Integration
• Decoding Secure AI Deployment in Cloud Environments
  Securing artificial intelligence deployments in cloud environments requires a comprehensive, multi-layered approach addressing unique challenges across physical, network, compute, storage, and application layers. This comprehensive examination explores the int…
  datacite Goyal, Bhaskar 2025 置信度 0.66 Cloud security; artificial intelligence; identity management; encryption; regulatory compliance; zero trust architecture
• Decoding Secure AI Deployment in Cloud Environments
  Securing artificial intelligence deployments in cloud environments requires a comprehensive, multi-layered approach addressing unique challenges across physical, network, compute, storage, and application layers. This comprehensive examination explores the int…
  datacite Goyal, Bhaskar 2025 置信度 0.66 Cloud security; artificial intelligence; identity management; encryption; regulatory compliance; zero trust architecture
• Quantum-Resistant Cryptographic Protocols in AI-Optimized Payment Reconciliation Systems
  This article presents an innovative hybrid architecture that integrates quantum-resistant cryptography with artificial intelligence to revolutionize global payment and reconciliation systems. The proposed article framework addresses the dual challenges of pote…
  datacite Thakur, Aparna 2025 置信度 0.66 Quantum-resistant cryptography; AI-optimized reconciliation; Lattice-based encryption; Federated learning; Post-quantum finance
• Quantum-Resistant Cryptographic Protocols in AI-Optimized Payment Reconciliation Systems
  This article presents an innovative hybrid architecture that integrates quantum-resistant cryptography with artificial intelligence to revolutionize global payment and reconciliation systems. The proposed article framework addresses the dual challenges of pote…
  datacite Thakur, Aparna 2025 置信度 0.66 Quantum-resistant cryptography; AI-optimized reconciliation; Lattice-based encryption; Federated learning; Post-quantum finance
• Artificial Intelligence and Machine Learning- Enabled Security Framework for Data Privacy in Cloud Computing
  The way in which Cloud computing has changed data storage and service delivery has also posed serious threats to privacy and security of data. The conventional encryption and rule-based intrusion detection systems can still not provide reasonable protection ag…
  datacite Eman Jabbar Ubaid 2026 置信度 0.66 Cloud computingdata privacyanomaly detectionmachine learningdeep learning
• Artificial Intelligence and Machine Learning- Enabled Security Framework for Data Privacy in Cloud Computing
  The way in which Cloud computing has changed data storage and service delivery has also posed serious threats to privacy and security of data. The conventional encryption and rule-based intrusion detection systems can still not provide reasonable protection ag…
  datacite Eman Jabbar Ubaid 2026 置信度 0.66 Cloud computingdata privacyanomaly detectionmachine learningdeep learning
• An Energy Efficient Clustering Algorithm for Network Lifetime in Wireless Sensor Network
  In wireless sensor networks, information aggregation accept a fundamental part in lessening essentialness use. Starting late, investigate has focused on secure information aggregation due to the open and disagreeable condition passed on. The Homomorphic Encryp…
  datacite Khuspare, Madhuri N., Khobragade, Dr. Awani S. 2021 置信度 0.66 Sensor NodesCluster HeadBase StationWireless Sensor NetworksCache Based System
• An Energy Efficient Clustering Algorithm for Network Lifetime in Wireless Sensor Network
  In wireless sensor networks, information aggregation accept a fundamental part in lessening essentialness use. Starting late, investigate has focused on secure information aggregation due to the open and disagreeable condition passed on. The Homomorphic Encryp…
  datacite Khuspare, Madhuri N., Khobragade, Dr. Awani S. 2021 置信度 0.66 Sensor NodesCluster HeadBase StationWireless Sensor NetworksCache Based System
• Homomorphic Encryption-Backed Collaborative Learning Pipelines for SovereignClinical Intelligence Across Hospital Networks
  datacite Boga, Vikram 2025 置信度 0.66
• Homomorphic Encryption-Backed Collaborative Learning Pipelines for SovereignClinical Intelligence Across Hospital Networks
  datacite Boga, Vikram 2025 置信度 0.66
• Data Privacy Engineering in Cloud-Native Environments: Integrating DevPrivOps, Risk Modeling, and Privacy-Enhancing Technologies
  The rapid adoption of cloud-native architectures has fundamentally transformed how modern applications are designed, developed, deployed, and scaled, enabling unprecedented levels of agility, elasticity, and resilience. However, this paradigm shift has simulta…
  datacite Seetala, Srinivasa Rao 2026 置信度 0.66 Cloud-native computing; Data privacy engineering; DevPrivOps; Privacy-by-design; GDPR; Data governance; Differential privacy; Secure data pipelines; Privacy risk assessment; Cloud security
• Data Privacy Engineering in Cloud-Native Environments: Integrating DevPrivOps, Risk Modeling, and Privacy-Enhancing Technologies
  The rapid adoption of cloud-native architectures has fundamentally transformed how modern applications are designed, developed, deployed, and scaled, enabling unprecedented levels of agility, elasticity, and resilience. However, this paradigm shift has simulta…
  datacite Seetala, Srinivasa Rao 2026 置信度 0.66 Cloud-native computing; Data privacy engineering; DevPrivOps; Privacy-by-design; GDPR; Data governance; Differential privacy; Secure data pipelines; Privacy risk assessment; Cloud security
• The Blind Machine: An End-to-End Platform for Privacy-Preserving Genomic Computation with Homomorphic Encryption
  Many scientific questions require computing statistics across datasets that cannot be pooled because the underlying records contain sensitive information that cannot be shared. Homomorphic encryption enables computation directly on encrypted data without expos…
  datacite Özmen, Barış 2026 置信度 0.66 homomorphic encryptionprivacy-preserving computationGenomicsCryptography
• The Blind Machine: An End-to-End Platform for Privacy-Preserving Genomic Computation with Homomorphic Encryption
  Many scientific questions require computing statistics across datasets that cannot be pooled because the underlying records contain sensitive information that cannot be shared. Homomorphic encryption enables computation directly on encrypted data without expos…
  datacite Özmen, Barış 2026 置信度 0.66 homomorphic encryptionprivacy-preserving computationGenomicsCryptography
• Privacy-Preserving Federated Query Processing Across Distributed Cloud Data Platforms
  The rapid adoption of multi-cloud data platforms has enabled organizations to perform large-scale distributed analytics while complying with regional data governance requirements. However, existing federated query processing frameworks often prioritize perform…
  datacite Shankar das Boddu 2026 置信度 0.66
• Privacy-Preserving Federated Query Processing Across Distributed Cloud Data Platforms
  The rapid adoption of multi-cloud data platforms has enabled organizations to perform large-scale distributed analytics while complying with regional data governance requirements. However, existing federated query processing frameworks often prioritize perform…
  datacite Shankar das Boddu 2026 置信度 0.66
• Deterministic homomorphic identity tokens for privacy-preserving attribute-based authentication
  Traditional multi-factor authentication (MFA) schemes, despite their layered defences, have been compromised in several common vulnerabilities and exposures (CVEs) due to their sequential verification process, which allows adversaries to target individual iden…
  datacite Tripathi, Shashank Shekher, Wöhnert, Kai Hendrik, Skwarek, Volker 2026 置信度 0.66 identityauthenticationprivacy004: Informatik
• VPFL: A verifiable privacy-preserving federated learning scheme for edge computing systems
  Federated learning for edge computing is a promising solution in the data booming era, which leverages the computation ability of each edge device to train local models and only shares the model gradients to the central server. However, the frequently transmit…
  datacite J Zhang, Y Liu, D Wu, S Lou 等 2026 置信度 0.66 DesignCybersecurity and privacyDistributed computing and systems softwareCommunications engineeringInformation and computing sciences
• Flexible Parallel Radix-4 MDC NTT for FHE
  Fully Homomorphic Encryption (FHE) is a promising technology that allows calculations to be performed on encrypted data. However, its widespread adoption is hindered by high computational requirements. In this paper, we present a design-time flexible FPGA acce…
  datacite Stelzer, Tobias, Karl, Patrick, Seelos-Zankl, Andreas, :unav 2026 置信度 0.66 CGGICKKSFully homomorphic encryptionmultipath delay commutatornumber theoretic transform
• TEMPORAL ROTATION SECURITY PROTOCOL (TRSP) Physics-First Cryptographic Architecture: Time as the Fundamental Security Parameter
  ABSTRACT: Temporal Rotation Security Protocol (TRSP) v3 — Physics-First Cryptographic Architecture: Time as the Fundamental Quantum-Resistant Security Parameter Concept in development since at least November 2019. First complete public documentation: 2026. Ver…
  datacite Mehmetaj, Ilir 2026 置信度 0.66 temporal rotation cryptographyphysics-first security architecturequantum-resistant key rotationtime-based cryptographic protocolCRATON foundational trust layer
• ФЕДЕРАТИВНОЕ ОБУЧЕНИЕ ДЛЯ ОБНАРУЖЕНИЯ КИБЕРУГРОЗ С СОХРАНЕНИЕМ КОНФИДЕНЦИАЛЬНОСТИ ДАННЫХ В КОРПОРАТИВНЫХ СЕТЯХ
  Аннотация. В настоящей статье рассматривается проблема централизованного обучения моделей обнаружения киберугроз, требующего агрегации конфиденциальных данных сетевого трафика от множества организаций-участников. Показано, что традиционный подход к обучению на…
  datacite Dupley, Maxim 2026 置信度 0.66
• ФЕДЕРАТИВНОЕ ОБУЧЕНИЕ ДЛЯ ОБНАРУЖЕНИЯ КИБЕРУГРОЗ С СОХРАНЕНИЕМ КОНФИДЕНЦИАЛЬНОСТИ ДАННЫХ В КОРПОРАТИВНЫХ СЕТЯХ
  Аннотация. В настоящей статье рассматривается проблема централизованного обучения моделей обнаружения киберугроз, требующего агрегации конфиденциальных данных сетевого трафика от множества организаций-участников. Показано, что традиционный подход к обучению на…
  datacite Dupley, Maxim 2026 置信度 0.66
• Low-Memory Homomorphic ResNet-20
  Machine Learning-as-a-Service (MLaaS) has become a dominant paradigm for deploying advanced artificial intelligence models, enabling users to leverage powerful cloud-hosted classifiers without the need for substantial local computational resources. However, th…
  datacite Mrs. Vaishali Lahire, Kishori Ghule 2026 置信度 0.66
• Low-Memory Homomorphic ResNet-20
  Machine Learning-as-a-Service (MLaaS) has become a dominant paradigm for deploying advanced artificial intelligence models, enabling users to leverage powerful cloud-hosted classifiers without the need for substantial local computational resources. However, th…
  datacite Mrs. Vaishali Lahire, Kishori Ghule 2026 置信度 0.66
• A SCALABLE PRIVACY-PRESERVING DATA MINING FRAMEWORK FOR MULTI-SITE CLOUD ENVIRONMENTS
  The increasing adoption of cloud-based data analytics has enabled organizations to perform large-scale data mining using distributed resources; however, this raises several concerns about data privacy, security, and legal/compliance issues with regard to cloud…
  datacite ANKITA SINGH, KANIKA GARG 2026 置信度 0.66 Privacy-Preserving Data Mining; Homomorphic Encryption; Secure Aggregation; Multi-Site Data Analytics; Cloud Computing; Data Privacy
• A SCALABLE PRIVACY-PRESERVING DATA MINING FRAMEWORK FOR MULTI-SITE CLOUD ENVIRONMENTS
  The increasing adoption of cloud-based data analytics has enabled organizations to perform large-scale data mining using distributed resources; however, this raises several concerns about data privacy, security, and legal/compliance issues with regard to cloud…
  datacite ANKITA SINGH, KANIKA GARG 2026 置信度 0.66 Privacy-Preserving Data Mining; Homomorphic Encryption; Secure Aggregation; Multi-Site Data Analytics; Cloud Computing; Data Privacy
• Privacy Rights in the Digital Age: Challenges, Opportunities, and Future Horizons
  Privacy, as one of the most fundamental human rights, has undergone profound paradigm shifts in the transition from the industrial age to the digital age. While the traditional concept of privacy was based on the "right to be let alone" and the Inviolability o…
  datacite Taherimanesh, Mehdi 2026 置信度 0.66 Digital Privacy, Data Rights, Artificial Intelligence, Surveillance Capitalism, Cryptography, Information Technology Law
• Privacy Rights in the Digital Age: Challenges, Opportunities, and Future Horizons
  Privacy, as one of the most fundamental human rights, has undergone profound paradigm shifts in the transition from the industrial age to the digital age. While the traditional concept of privacy was based on the "right to be let alone" and the Inviolability o…
  datacite Taherimanesh, Mehdi 2026 置信度 0.66 Digital Privacy, Data Rights, Artificial Intelligence, Surveillance Capitalism, Cryptography, Information Technology Law
• Composable Privacy: Integrating Selective Disclosure Credentials with Fully Homomorphic Encryption
  Privacy-preserving systems have traditionally faced a fundamental tradeoff between data utility and confidentiality. Selective Disclosure Credentials (SDCs) enable users to prove specific attributes without revealing underlying personal information, while Full…
  datacite Fernandes, Aldrid 2026 置信度 0.66
• Composable Privacy: Integrating Selective Disclosure Credentials with Fully Homomorphic Encryption
  Privacy-preserving systems have traditionally faced a fundamental tradeoff between data utility and confidentiality. Selective Disclosure Credentials (SDCs) enable users to prove specific attributes without revealing underlying personal information, while Full…
  datacite Fernandes, Aldrid 2026 置信度 0.66
• VIFP: Shape-Hiding Tree Mining on Encrypted Data via Virtual-Interval FP-Growth
  Privacy-preserving frequent itemset mining has been studied for more than two decades, mainlythrough secure candidate counting, horizontally or vertically partitioned protocols, outsourced en-crypted support computation, and partial homomorphic outsourcing. Ho…
  datacite Van Ha, Minh Quan 2026 置信度 0.66
• Fully Homomorphic Collaborative Learning for Safe Cross-Healthcare Institution Development and Implementation of Foundation Models
  europepmc 2026 置信度 0.80
• Security, Privacy and Regulatory Governance in Digital Payments. A Systematic Review and Cross-Architecture Framework for PIX, Blockchain, and Central Bank Digital Currencies
  europepmc 2026 置信度 0.80
• A Framework for Secure Healthcare Cloud Architecture for Security Threat Mitigation and Regulatory Compliance
  europepmc 2026 置信度 0.80
• Privacy Analytics in Accounting Information Systems
  europepmc 2026 置信度 0.80
• A Privacy-Aware Framework for Stress Prediction Based on Secure Computational Intelligence
  europepmc 2025 置信度 0.80
• Privacy-Preserving Patent Matching Model
  europepmc 2026 置信度 0.80
• Exact Multi-Task Aggregation with Confidential Queries and Designated Recovery
  europepmc 2026 置信度 0.80
• <em>ppAIsec</em>: Privacy-Preserving Artificial Intelligence Models in Healthcare Security—A Synthesis of AI Frameworks
  europepmc 2026 置信度 0.80
• Masked B-Tree Data Structure
  europepmc 2025 置信度 0.80
• Decentralized Trust Model for Vehicle Ad-Hoc Networks (VANETs) with 5G Integration: A Blockchain-Based Approach for Enhanced Security and Privacy in Intelligent Transportation Systems
  europepmc 2025 置信度 0.80
• Multi_key Homomorphic Crypto and Multiscale Transformer Learning Secure Data Aggregation in Wsn for Smart Agriculture
  europepmc 2025 置信度 0.80
• GPU-NTT and Karatsuba Co-Optimization forHigh-Throughput Polynomial MultiplicationAcceleration
  europepmc 2026 置信度 0.80
• Hide and Seek: Privacy-Preserving Artificial Intelligence with a Feasibility Study in Rare Disease Diagnosis
  europepmc 2026 置信度 0.80
• A Security-Oriented Privacy-Preserving Framework for Efficient Medical Record Search in Telemedicine
  europepmc 2025 置信度 0.80
• CCA-attacks on lattice-based encryption-decryption schemes
  europepmc 2025 置信度 0.80
• Survey of Privacy Preserving Techniques for Distributed Learning in an IoT Network
  europepmc 2025 置信度 0.80
• An Integrated Framework for Prescriptive Analytics and Interactive Visualization to Optimize Financial fraud detection in High-Volume Digital Markets
  europepmc 2025 置信度 0.80
• Cryptography in Secure Cloud Computing
  europepmc 2025 置信度 0.80
• Advancing Trustworthy AI in the Cloud Era: From Generative Models to Privacy-Preserving MLOps
  europepmc 2025 置信度 0.80
• LAPMS: A Lightweight and Privacy-Preserving Management Scheme for Secure Vehicle Platoons
  europepmc 2025 置信度 0.80
• Privacy-Preserving Natural Language Processing for Clinical Notes
  europepmc 2025 置信度 0.80
• Privacy Risk Assessment Frameworks for Large-Scale Medical Datasets Using Computational Metrics
  preprints 2025 置信度 0.74
• Secure Aggregation-Based Big Data Analysis and Power Prediction Model for Photovoltaic Systems: A Multi-Layered Approach
  europepmc 2024 置信度 0.80
• Enhancing Secure Multi-Party Computation with Damgård-Jurik and NIZK Proofs: A Lightweight Protocol for Scalable Aggregation
  preprints 2025 置信度 0.74
• Personalized Medical Approach in Gastrointestinal Surgical Oncology: Current Trends and Future Perspectives
  preprints 2025 置信度 0.74
• Privacy-Preserving Data Analytics in 5G-Enabled IoT for the Financial Industry
  preprints 2025 置信度 0.74
• Privacy-preserving AUC Computation in Distributed Machine Learning with PHT-meDIC
  preprints 2025 置信度 0.74
• Privacy Aware Data Aggregation with Application in Voting Systems
  preprints 2025 置信度 0.74
• Differentially Private Distributed Inference for Multicenter Clinical Studies
  preprints 2025 置信度 0.74
• Research on data security protection strategy in electricity information acquisition system
  europepmc 2024 置信度 0.80
• A novel homomorphic polynomial public key encapsulation algorithm
  preprints 2023 置信度 0.74
• A Lightweight Transformation Method for Protecting the Privacy of Image Training in Classification.
  europepmc 2024 置信度 0.80
• Towards a new standard in genomic data privacy: a realization of owner-governance
  europepmc 2024 置信度 0.80
• A Verifiable Privacy-Preserving Data Aggregation Scheme with Illegal Data Detection for Infectious Disease Surveillance Systems
  europepmc 2024 置信度 0.80
• Secure Cloud Computing By A dual-Layer Encryption Mechanism
  preprints 2023 置信度 0.74
• Technical Sandbox for a Global Patient co-Owned Cloud (GPOC)
  preprints 2024 置信度 0.74
• Using encrypted genotypes and phenotypes for collaborative genomic analyses to maintain data confidentiality
  preprints 2023 置信度 0.74
• Technical Sandbox for a Global Patient co-Owned Cloud (GPOC)
  preprints 2024 置信度 0.74
• Secure and Efficient Sharing of Model Insights between Commercial Large Language Models
  preprints 2024 置信度 0.74