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• Authenticable quantum secret sharing based on special entangled state.
  europepmc 2025 置信度 0.80
• The role of multimodality in clinical disease diagnosis: advances, challenges, and opportunities.
  europepmc 2026 置信度 0.80
• Scalable and Privacy-Preserving Federated Principal Component Analysis.
  europepmc 2023 置信度 0.80
• E-Research Institutional Cloud Architecture (ERICA): An Orchestration Meta-Framework for Establishing Trusted Research Environments Using Public Cloud Computing.
  europepmc 2026 置信度 0.80
• Delegated multi-party private set intersections from extendable output functions.
  europepmc 2025 置信度 0.80
• Federated Learning in Smart Healthcare: A Comprehensive Review on Privacy, Security, and Predictive Analytics with IoT Integration.
  Federated learning (FL) is revolutionizing healthcare by enabling collaborative machine learning across institutions while preserving patient privacy and meeting regulatory standards. This review delves into FL's applications within smart health systems, parti…
  pubmed Abbas SR, Abbas Z, Zahir A, Lee SW 2024 置信度 0.82
• PP-GWAS: Privacy Preserving Multi-Site Genome-wide Association Studies.
  europepmc 2025 置信度 0.80
• Connected, digitalized wire arc additive manufacturing: utilizing data in the internet of production to enable industrie 4.0.
  europepmc 2025 置信度 0.80
• Explainable federated learning scheme for secure healthcare data sharing.
  europepmc 2024 置信度 0.80
• Design of an iterative method for adaptive federated intrusion detection for energy-constrained edge-centric 6G IoT cyber-physical systems.
  europepmc 2025 置信度 0.80
• Propensity score matching and stratification using multiparty data without pooling.
  europepmc 2023 置信度 0.80
• A lattice-integrated AES framework for ultra-secure biometric protection on resource-constrained edge devices.
  europepmc 2026 置信度 0.80
• Genomic privacy preservation in genome-wide association studies: taxonomy, limitations, challenges, and vision.
  Genome-wide association studies (GWAS) serve as a crucial tool for identifying genetic factors associated with specific traits. However, ethical constraints prevent the direct exchange of genetic information, prompting the need for privacy preservation solutio…
  pubmed Aherrahrou N, Tairi H, Aherrahrou Z 2024 置信度 0.82
• ChaQra: a cellular unit of the Indian quantum network.
  europepmc 2024 置信度 0.80
• SENSH: a blockchain-based searchable encrypted data sharing scheme in smart healthcare.
  europepmc 2025 置信度 0.80
• AI-driven multimodal colorimetric analytics for biomedical and behavioral health diagnostics.
  The exponential growth of multi-scale biomedical and behavioral data introduces both challenges and opportunities for Image 1-driven analytics. Effectively managing the complexity and variability of these data sources requires advanced computational techniques…
  europepmc 2025 置信度 0.80
• PriMPSO: A Privacy-Preserving Multiagent Particle Swarm Optimization Algorithm.
  europepmc 2023 置信度 0.80
• Autonomous nursing professional development framework using blockchain technology.
  europepmc 2026 置信度 0.80
• A novel obfuscation method based on majority logic for preventing unauthorized access to binary deep neural networks.
  europepmc 2025 置信度 0.80
• Federated Machine Learning, Privacy-Enhancing Technologies, and Data Protection Laws in Medical Research: Scoping Review.
  europepmc 2023 置信度 0.80
• Secure electronic health record access control via blockchain, dual-attribute encryption, and large language model-based attribute extraction.
  europepmc 2026 置信度 0.80
• mHealth Systems Need a Privacy-by-Design Approach: Commentary on "Federated Machine Learning, Privacy-Enhancing Technologies, and Data Protection Laws in Medical Research: Scoping Review".
  europepmc 2023 置信度 0.80
• COLLAGENE enables privacy-aware federated and collaborative genomic data analysis.
  Growing regulatory requirements set barriers around genetic data sharing and collaborations. Moreover, existing privacy-aware paradigms are challenging to deploy in collaborative settings. We present COLLAGENE, a tool base for building secure collaborative gen…
  pubmed Li W, Kim M, Zhang K, Chen H 等 2023 置信度 0.82
• A critical analysis of deployed use cases for quantum key distribution and comparison with post-quantum cryptography.
  europepmc 2025 置信度 0.80
• A Refined Supervision Model of Rice Supply Chain Based on Multi-Blockchain.
  europepmc 2022 置信度 0.80
• A federated incremental blockchain framework with privacy preserving XAI optimization for securing healthcare data.
  europepmc 2025 置信度 0.80
• Unraveling the Ethical Enigma: Artificial Intelligence in Healthcare.
  The integration of artificial intelligence (AI) into healthcare promises groundbreaking advancements in patient care, revolutionizing clinical diagnosis, predictive medicine, and decision-making. This transformative technology uses machine learning, natural la…
  pubmed Jeyaraman M, Balaji S, Jeyaraman N, Yadav S 2023 置信度 0.82
• The evolving privacy and security concerns for genomic data analysis and sharing as observed from the iDASH competition.
  europepmc 2022 置信度 0.80
• A secure and privacy preserved data aggregation scheme in IoMT.
  europepmc 2024 置信度 0.80
• Privacy-preserving model evaluation for logistic and linear regression using homomorphically encrypted genotype data.
  europepmc 2024 置信度 0.80
• Towards Secure Internet of Things: A Coercion-Resistant Attribute-Based Encryption Scheme with Policy Revocation.
  europepmc 2025 置信度 0.80
• GEN-RWD Sandbox: bridging the gap between hospital data privacy and external research insights with distributed analytics.
  europepmc 2024 置信度 0.80
• Privacy-Preserving Federated Survival Support Vector Machines for Cross-Institutional Time-To-Event Analysis: Algorithm Development and Validation.
  europepmc 2024 置信度 0.80
• Federated Learning in Public Health: A Systematic Review of Decentralized, Equitable, and Secure Disease Prevention Approaches.
  pubmed Shah ST, Ali Z, Waqar M, Kim A 2025 置信度 0.82
• Commitment Schemes from OWFs with Applications to Quantum Oblivious Transfer.
  europepmc 2025 置信度 0.80
• Federation, not centralization: a new paradigm for electronic health record-based critical care research.
  europepmc 2026 置信度 0.80
• Deep Learning Applications in Clinical Cancer Detection: A Review of Implementation Challenges and Solutions.
  Deep learning (DL) has revolutionized cancer detection accuracy, speed, and accessibility. Leveraging sophisticated algorithms, DL has demonstrated transformative potential across diverse applications, including imaging-based diagnostics and genomic analysis, …
  pubmed Yao IZ, Dong M, Hwang WYK 2025 置信度 0.82
• Representative Ring Signature Algorithm Based on Smart Contract.
  europepmc 2022 置信度 0.80
• A privacy preserving and auditable blockchain framework for seccure securites trading.
  europepmc 2025 置信度 0.80
• Sequre: a high-performance framework for rapid development of secure bioinformatics pipelines.
  europepmc 2022 置信度 0.80
• Yves Moreau has received the 2023 Einstein Foundation Individual Award for Promoting Quality in Research.
  europepmc 2024 置信度 0.80
• sfkit: a web-based toolkit for secure and federated genomic analysis.
  europepmc 2023 置信度 0.80
• FedEff: efficient federated learning with optimal local epochs for heterogeneous clients.
  Federated Learning (FL) enables collaborative model training without centralized data sharing; however, its efficiency often degrades under system and statistical heterogeneity across clients. Increasing the number of local epochs per round can enhance efficie…
  europepmc K Narmadha, P. Varalakshmi 2025 置信度 0.80 Computer scienceFederated learningSelection (genetic algorithm)Divergence (linguistics)Computation
• Privacy-Preserving Collaborative Diabetes Prediction in Heterogeneous Health Care Systems: Algorithm Development and Validation of a Secure Federated Ensemble Framework.
  europepmc 2026 置信度 0.80
• Decentralizing Health Care: History and Opportunities of Web3.
  europepmc 2024 置信度 0.80
• Privacy-Preserving Prediction of Postoperative Mortality in Multi-Institutional Data: Development and Usability Study.
  europepmc 2024 置信度 0.80
• A Semi-Quantum Private Comparison Base on W-States.
  europepmc 2023 置信度 0.80
• Multimedia Fusion Privacy Protection Algorithm Based on IoT Data Security under Network Regulations.
  europepmc 2022 置信度 0.80
• HIV-1 and Artificial Intelligence: From Molecular Insight to Population Impact.
  europepmc 2025 置信度 0.80
• Round-Efficient Secure Inference Based on Masked Secret Sharing for Quantized Neural Network.
  europepmc 2023 置信度 0.80
• Artificial intelligence in medicine: from molecular data analysis to clinical decision-making.
  europepmc 2026 置信度 0.80
• Combining Real-World and Clinical Trial Data Through Privacy-Preserving Record Linkage: Opportunities and Challenges-A Narrative Review.
  europepmc 2025 置信度 0.80
• A Study on the Interoperability Technology of Digital Identification Based on WACI Protocol with Multiparty Distributed Signature.
  europepmc 2023 置信度 0.80
• A Dickson polynomial based group key agreement authentication scheme for ensuring conditional privacy preservation and traceability in VANETs.
  europepmc 2025 置信度 0.80
• The BioRef Infrastructure, a Framework for Real-Time, Federated, Privacy-Preserving, and Personalized Reference Intervals: Design, Development, and Application.
  europepmc 2023 置信度 0.80
• Decentralized Proof-of-Location systems for trust, scalability, and privacy in digital societies.
  europepmc 2025 置信度 0.80
• Blockchain-Based Information Security Protection Mechanism for the Traceability of Intellectual Property Transactions.
  europepmc 2025 置信度 0.80
• Building Public Health Data Dashboards: Tutorial Playbook.
  europepmc 2026 置信度 0.80
• SQUiD: ultra-secure storage and analysis of genetic data for the advancement of precision medicine.
  europepmc 2024 置信度 0.80
• Revolutionizing Medical Data Sharing Using Advanced Privacy-Enhancing Technologies: Technical, Legal, and Ethical Synthesis.
  Multisite medical data sharing is critical in modern clinical practice and medical research. The challenge is to conduct data sharing that preserves individual privacy and data utility. The shortcomings of traditional privacy-enhancing technologies mean that i…
  pubmed Scheibner J, Raisaro JL, Troncoso-Pastoriza JR, Ienca M 等 2021 置信度 0.82
• Mamba-fusion for privacy-preserving disease prediction.
  Accurate disease prediction is essential for improving patient outcomes. Privacy regulations like GDPR and HIPAA limit data sharing, hindering the development of robust predictive models across institutions. FL and multi-modal fusion frameworks counter these p…
  pubmed Jabbar MK, Jianjun H, Jabbar A, Bilal A 2025 置信度 0.82
• New Approach to Privacy-Preserving Clinical Decision Support Systems for HIV Treatment.
  europepmc 2022 置信度 0.80
• Controlled quantum authentication confidential communication protocol for smart healthcare.
  europepmc 2025 置信度 0.80
• Combating errors in quantum communication: an integrated approach.
  europepmc 2023 置信度 0.80
• On the Asymptotic Capacity of Information-Theoretic Privacy-Preserving Epidemiological Data Collection.
  europepmc 2023 置信度 0.80
• Understanding privacy concerns in ChatGPT: A data-driven approach with LDA topic modeling.
  europepmc 2024 置信度 0.80
• Transforming neonatal care through informatics: A review of artificial intelligence, data, and implementation considerations.
  Significant strides have been made in utilizing data, information, and knowledge to enhance neonatal outcomes. This review examines how data informatics, encompassing electronic health records (EHRs), data standards, and artificial intelligence (AI), has facil…
  pubmed Barrett R, Lawler B, Liu S, Park WY 等 2025 置信度 0.82
• TinyML-Based Lightweight AI Healthcare Mobile Chatbot Deployment.
  europepmc 2024 置信度 0.80
• vantage6
  Vantage6 stands for privacy preserving federated learning infrastructure for secure insight exchange. The project is inspired by the Personal Health Train (PHT) concept. In this analogy vantage6 is the tracks and stations. Compatible algorithms are the trains,…
  datacite Martin, Frank, Beusekom, Bart, Leurs, Richard, Sieswerda, Melle 等 2026 置信度 0.66 federated learningmachine learningdata analysissecure multiparty computationprivacy enhancing technology
• vantage6
  Vantage6 stands for privacy preserving federated learning infrastructure for secure insight exchange. The project is inspired by the Personal Health Train (PHT) concept. In this analogy vantage6 is the tracks and stations. Compatible algorithms are the trains,…
  datacite Martin, Frank, Beusekom, Bart, Leurs, Richard, Sieswerda, Melle 等 2026 置信度 0.66 federated learningmachine learningdata analysissecure multiparty computationprivacy enhancing technology
• vantage6
  Vantage6 stands for privacy preserving federated learning infrastructure for secure insight exchange. The project is inspired by the Personal Health Train (PHT) concept. In this analogy vantage6 is the tracks and stations. Compatible algorithms are the trains,…
  datacite Martin, Frank, Beusekom, Bart, Leurs, Richard, Sieswerda, Melle 等 2026 置信度 0.66 federated learningmachine learningdata analysissecure multiparty computationprivacy enhancing technology
• vantage6
  Vantage6 stands for privacy preserving federated learning infrastructure for secure insight exchange. The project is inspired by the Personal Health Train (PHT) concept. In this analogy vantage6 is the tracks and stations. Compatible algorithms are the trains,…
  datacite Martin, Frank, Beusekom, Bart, Leurs, Richard, Sieswerda, Melle 等 2026 置信度 0.66 federated learningmachine learningdata analysissecure multiparty computationprivacy enhancing technology
• vantage6
  Vantage6 stands for privacy preserving federated learning infrastructure for secure insight exchange. The project is inspired by the Personal Health Train (PHT) concept. In this analogy vantage6 is the tracks and stations. Compatible algorithms are the trains,…
  datacite Martin, Frank, Beusekom, Bart, Leurs, Richard, Sieswerda, Melle 等 2026 置信度 0.66 federated learningmachine learningdata analysissecure multiparty computationprivacy enhancing technology
• vantage6
  Vantage6 stands for privacy preserving federated learning infrastructure for secure insight exchange. The project is inspired by the Personal Health Train (PHT) concept. In this analogy vantage6 is the tracks and stations. Compatible algorithms are the trains,…
  datacite Martin, Frank, Beusekom, Bart, Leurs, Richard, Sieswerda, Melle 等 2026 置信度 0.66 federated learningmachine learningdata analysissecure multiparty computationprivacy enhancing technology
• vantage6
  Vantage6 stands for privacy preserving federated learning infrastructure for secure insight exchange. The project is inspired by the Personal Health Train (PHT) concept. In this analogy vantage6 is the tracks and stations. Compatible algorithms are the trains,…
  datacite Martin, Frank, Beusekom, Bart, Leurs, Richard, Sieswerda, Melle 等 2026 置信度 0.66 federated learningmachine learningdata analysissecure multiparty computationprivacy enhancing technology
• Privacy-Preserving Federated Learning Framework for ICU Patient Monitoring and Decision Support in Hospitals
  The increasing digitization of healthcare systems has led to the generation of large-scale ICU patient data across hospitals. However, centralized machine learning approaches pose significant privacy risks, limiting data sharing across institutions. This paper…
  datacite Mr. B. Sundaresan, Bernus A, Jayamadhavan V, Sam Benny J Department of Computer Science & Engineering Velammal Institute of Technology, Panchetti, DEPARTMENT OF ARTIFICIAL INTELLIGENCE AND DATA SCIENCE R.M.K. College of Engineering and Technology, MISSILE MAN SCIENTIFIC AND RESEARCH PUBLICATIONS 2026 置信度 0.66
• Privacy-Preserving Federated Learning Framework for ICU Patient Monitoring and Decision Support in Hospitals
  The increasing digitization of healthcare systems has led to the generation of large-scale ICU patient data across hospitals. However, centralized machine learning approaches pose significant privacy risks, limiting data sharing across institutions. This paper…
  datacite Mr. B. Sundaresan, Bernus A, Jayamadhavan V, Sam Benny J Department of Computer Science & Engineering Velammal Institute of Technology, Panchetti, DEPARTMENT OF ARTIFICIAL INTELLIGENCE AND DATA SCIENCE R.M.K. College of Engineering and Technology, MISSILE MAN SCIENTIFIC AND RESEARCH PUBLICATIONS 2026 置信度 0.66
• CryptDough: A Unified Analytics Engine for Secure Multiparty Computation
  We present CryptDough, a unified analytics engine for secure multiparty computation (MPC). CryptDough enables multiple distrusting parties to jointly execute a data analysis pipeline on their private inputs and learn nothing beyond the result (e.g., aggregate …
  datacite Faisal, Muhammad, Lanz, Alessandra, Buxbaum, Sam, Godel, Adam 等 2026 置信度 0.66 Cryptography and Security (cs.CR)Operating Systems (cs.OS)FOS: Computer and information sciences
• Fast Bounded-Independence Functions and Their Duals
  We continue the study of fast functions, computable by linear-size circuits, that share useful properties of random functions. Motivated by cryptographic applications, we generalize and improve on previous results in this area, obtaining the following results:…
  datacite Brehm, Martijn, Ishai, Yuval, Resch, Nicolas 2026 置信度 0.66 Linear codeshash function familiesefficient encodingsecure computationTheory of computation → Cryptographic primitives
• Compressing Correlations via Secret Replication: PCFs from Symmetric Cryptography
  We revisit the question of securely compressing multiparty correlations using only symmetric cryptography. A linear correlation C, defined by a linear subspace C ⊆ 𝔽ⁿ, samples a secret random 𝐜 ∈ C and assigns to each party a fixed subset of the entries of �…
  datacite Ishai, Yuval, Krawczyk, Hugo, Rabin, Tal 2026 置信度 0.66 Pseudorandom correlation functionscorrelated randomnesssecure computationsymmetric cryptographyTheory of computation → Cryptographic primitives
• Blind Transpiler: An open-source library for universally blind and homomorphic quantum computations
  Blind quantum computation is a cryptographic primitive that allows a limited-capability client to delegate its complex computation to a remote server without revealing its data and/or computation. This branch of quantum cryptography has been bifurcated into tw…
  datacite Joshi, Mohit, Mishra, Manoj Kumar, Karthikeyan, S. 2026 置信度 0.66 Quantum Physics (quant-ph)FOS: Physical sciences
• Security Relaxations for Improving Secure Multiparty Computation
  Secure multi-party computation (MPC) is an important subfield of modern cryptography that allows multiple parties to jointly compute a function over their private inputs without revealing anything other than the function output. Over the last decade, many incr…
  datacite Liang, Mingyu 2022 置信度 0.66 CryptocurrencyCryptographyDifferential privacyOnion routingPrivate set union
• Service Assurance in Insecure Networks with Byzantine Adversaries
  This dissertation describes research into security threats in new communication environ- ments and methods to counter them. More specifically, we consider networks where some nodes perform an important application function such as routing, filtering, aggregati…
  datacite Rabinovich, Paul 2008 置信度 0.66 SecurityByzantineAdversaryPublish/subscribeSensor networks
• Scalable Secure Multiparty Computation
  Secure multiparty computation (MPC) allows a group of parties to collectively perform computation on their combined inputs while revealing nothing about their private inputs beyond what can be inferred from the output of the computation. Although early results…
  datacite McVicker, Daniel Alan 2024 置信度 0.66 BlockchainCryptographyMPCMultiparty ComputationSecurity
• A systematic overview on methods to protect sensitive data provided for various analyses
  In view of the various methodological developments regarding the protection of sensitive data, especially with respect to privacy-preserving computation and federated learning, a conceptual categorization and comparison between various methods stemming from di…
  datacite Templ, Matthias, Sariyar, Murat 2022 置信度 0.66 AnonymizationPrivacy-preserving computationFederated learningSynthetic data005: Computerprogrammierung, Programme und Daten
• Dynamic group key agreement for resource-constrained devices using blockchains
  Dynamic group key agreement (DGKA) protocols are one of the key security primitives to secure multiparty communications in decentralized and insecure environments while considering the instant changes in a communication group. However, with the ever-increasing…
  datacite Taçyıldız, Yaşar Berkay, Ermiş, Orhan, Gür, Gürkan, Alagöz, Fatih 2020 置信度 0.66 Group key agreementBlockchainIoTHyperledger fabric005: Computerprogrammierung, Programme und Daten
• CHRONOS: A Hardware-Assisted Phase-Decoupled Framework for Secure Federated Learning in IoT
  Federated learning enables collaborative training on IoT gateways without sharing raw data, yet gradients remain susceptible to inversion attacks. Existing Secure Multiparty Computation defenses impose prohibitive communication overhead, exceeding strict IoT l…
  datacite Dang, Hung 2026 置信度 0.66 Cryptography and Security (cs.CR)Distributed, Parallel, and Cluster Computing (cs.DC)FOS: Computer and information sciences
• Opportunistic Search in Disconnected Mobile Adhoc Network
  To design a social network based P2P content based file sharing system in disconnected Mobile Adhoc Networks in a privacy preserving manner for efficient file searching based on interest casting. As the mobile digital devices are carried by people that usually…
  datacite Kalpana, A. V., Prakash, R., Sundar, G. 2015 置信度 0.66 Adhoc networksp2p content based fileprivacysecure multiparty computation
• Opportunistic Search in Disconnected Mobile Adhoc Network
  To design a social network based P2P content based file sharing system in disconnected Mobile Adhoc Networks in a privacy preserving manner for efficient file searching based on interest casting. As the mobile digital devices are carried by people that usually…
  datacite Kalpana, A. V., Prakash, R., Sundar, G. 2015 置信度 0.66 Adhoc networksp2p content based fileprivacysecure multiparty computation
• Watermark Detection In Compressive Sensing Domain To Preserve Privacy
  We propose a compressive sensing based privacy preserving watermark detection framework that involves secure multiparty computation and the cloud. There are three parties in the proposed framework, the data holders (DH) of the potentially watermarked images, t…
  datacite S, Saranya, B, Sangeetha, M, Gayathri 2015 置信度 0.66 Compressive sensingwatermark detectionsecure signal processingsecure multiparty computationprivacy preserving.
• Watermark Detection In Compressive Sensing Domain To Preserve Privacy
  We propose a compressive sensing based privacy preserving watermark detection framework that involves secure multiparty computation and the cloud. There are three parties in the proposed framework, the data holders (DH) of the potentially watermarked images, t…
  datacite S, Saranya, B, Sangeetha, M, Gayathri 2015 置信度 0.66 Compressive sensingwatermark detectionsecure signal processingsecure multiparty computationprivacy preserving.
• Privacy-preserving schemes for electricity data analytics in smart grids
  The integration of information communication technologies into traditional power grids creates a new concept of ``smart grids". With various electricity data analytics applications in smart grids, the electricity industry is expected to operate more efficientl…
  datacite Tran, Hong Yen 2023 置信度 0.66 Privacy-preserving Data AnalyticsSecure Multiparty ComputationHomomorphic EncryptionFederated LearningLoad Forecasting
• The Complexity of Reliable and Secure Distributed Transactions
  The use of transactions in distributed systems dates back to the 70's. The last decade has also seen the proliferation of transactional systems. In the existing transactional systems, many protocols employ a centralized approach in executing a distributed tran…
  datacite Wang, Jingjing 2018 置信度 0.66 complexityfailuresdistributed transactionsnon-blocking atomic commitindulgent atomic commit
• Blockchain-based Decentralized Energy Systems: Advancing Scalability, Security, Privacy, and Interoperability
  As the global energy landscape evolves, there is a transformative shift towards Decentralised Energy Systems (DES), characterized by Distributed Energy Resources (DERs) and Smart Grid technologies. DES offers several opportunities, including enhanced energy ef…
  datacite Karumba, Samuel 2024 置信度 0.66 Blockchain TechnologyDecentralized Energy Systems (DES)ScalabilityCybersecurity and PrivacyInteroperability
• Bootstrapping Physical Security with Inertial Hardware Security Modules
  In the past decades, cryptographic advancements and techniques like formal verification have steadily improved software security. Meanwhile, the field of hardware security has not kept pace. Research has made progress in subfields such as resilience to Side-Ch…
  datacite Götte, Jan Sebastian 2026 置信度 0.66 hardware securitycybersecuritytamper sensing meshsecurity meshhardware security module
• New bounds on private simultaneous quantum message passing
  In the private simultaneous message (PSM) setting, $k$ players obtain inputs $x_i\in\{0,1\}^n$ and then each send messages to a referee, who should learn $f(x_1,...,x_k)$ but no other information about $(x_1,...,x_k)$. The PSM setting was introduced as a minim…
  datacite Girish, Uma, May, Alex, Parham, Natalie, Yuen, Henry 2026 置信度 0.66 Quantum Physics (quant-ph)FOS: Physical sciences
• On Randomness Complexity of 1-Private Protocols
  In the field of information-theoretic cryptography, randomness complexity is a key metric for protocols for private computation, that is, the number of random bits needed to realize the protocol. Although some general bounds are known, even for the relatively …
  datacite Dittmer, Samuel, Ostrovsky, Rafail 2026 置信度 0.66 limited independencebounded independencek-wise independenceH-wise independent sample spacessmall sample spaces
• Anonymous multi-party quantum computation with a third party
  We reconsider and modify the second secure multi-party quantum addition protocol proposed in our original work. We show that the protocol is an anonymous multi-party quantum addition protocol rather than a secure multi-party quantum addition protocol. Through …
  datacite Ji, Zhaoxu, Fan, Peiru, Rahman, Atta Ur, Zhang, Huanguo 2021 置信度 0.66 Quantum Physics (quant-ph)FOS: Physical sciences
• vantage6
  Vantage6 stands for privacy preserving federated learning infrastructure for secure insight exchange. The project is inspired by the Personal Health Train (PHT) concept. In this analogy vantage6 is the tracks and stations. Compatible algorithms are the trains,…
  datacite Martin, Frank, Beusekom, Bart, Leurs, Richard, Sieswerda, Melle 等 2026 置信度 0.66 federated learningmachine learningdata analysissecure multiparty computationprivacy enhancing technology
• Game-Theoretic Framework for Private Data Sharing in Vehicular Networks
  We present a novel game-theoretic framework designed to enhance privacy and scalability in decentralized vehicular data collection systems. The proposed hybrid architecture comprises vehicles that supply sensor data, independent servers that process data via s…
  datacite AlSaqabi, Yousef, Zhou, Yinan, Nawab, Faisal, Krishnamachari, Bhaskar 2026 置信度 0.66 Networking and Internet Architecture (cs.NI)Cryptography and Security (cs.CR)Computer Science and Game Theory (cs.GT)FOS: Computer and information sciencesFOS: Computer and information sciences