Collection and Analysis of Sensitive Data with Privacy Protection by a Distributed Randomized Response Protocol

Συγγραφείς: Faisal Imran, Rosa Meo

Πηγή: Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing. :1415-1424

Θεματικοί όροι: Statistics and Probability, Alternative medicine, Information privacy, FOS: Health sciences, Diagnostic Methods for COVID-19 Detection, Estimator, 7. Clean energy, Artificial Intelligence, Computer security, Health Sciences, FOS: Mathematics, Pathology, Privacy protection, Randomized Response, Local Differential Privacy, Contingency Tables, Distributed computation protocol, Differential Privacy, Statistical Methods for Sensitive Survey Questions, Privacy Preservation, Computer network, Randomized Response Technique, Statistics, Privacy-Preserving Techniques for Data Analysis and Machine Learning, 16. Peace & justice, Computer science, Infectious Diseases, Computer Science, Physical Sciences, Protocol (science), Sensitive Questions, Medicine, Stratified Sampling, Randomized response, Mathematics

Περιγραφή αρχείου: application/pdf

Perfectly Accurate Membership Inference by a Dishonest Central Server in Federated Learning

Συγγραφείς: Georg Pichler, Marco Romanelli, Leonardo Rey Vega, Pablo Piantanida

Πηγή: IEEE Transactions on Dependable and Secure Computing. 21:4290-4296

Θεματικοί όροι: FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial intelligence, Computer Science - Cryptography and Security, Computer Science - Artificial Intelligence, Set (abstract data type), Evolutionary biology, 02 engineering and technology, MNIST database, Epistemology, Contrast (vision), LEARNING, Adversarial Robustness in Deep Learning Models, Machine Learning (cs.LG), Deep Learning, Inference, Artificial Intelligence, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, FEDERATED, Data mining, Biology, NEURAL NET, Membership Inference Attacks, Chromatography, Sample (material), Privacy-Preserving Techniques for Data Analysis and Machine Learning, Deep learning, Computer science, FOS: Philosophy, ethics and religion, Programming language, Philosophy, Chemistry, Artificial Intelligence (cs.AI), Function (biology), Computer Science, Physical Sciences, Simple (philosophy), MEMBERSHIP INFERENCE, Cryptography and Security (cs.CR), Federated Learning, Training set

Περιγραφή αρχείου: application/pdf

Σύνδεσμος πρόσβασης: http://arxiv.org/abs/2203.16463
http://hdl.handle.net/11336/255711

From Barriers to Boosters: Optimizing Open Government Data through Publishing Guidelines and Data Protection Strategies

Συγγραφείς: Khadidja Bouchelouche, Abdessamedréda Ghomari, Leila Zemmouchi-Ghomari

Πηγή: Recent Research Reviews Journal. 3:56-69

Θεματικοί όροι: Data Quality Assessment and Improvement, Metric (unit), FOS: Political science, Social Sciences, FOS: Law, Management Science and Operations Research, Data management, Decision Sciences, Data science, Database, FOS: Economics and business, Open government, Artificial Intelligence, Evolution and Impact of E-Government Initiatives, Open Data, Data publishing, 11. Sustainability, Government (linguistics), Business, Political science, Semantic Web, Publishing, Marketing, Discoverability, Linked data, Open data, Privacy-Preserving Techniques for Data Analysis and Machine Learning, Data quality, 1. No poverty, Linguistics, 15. Life on land, Data governance, 16. Peace & justice, Computer science, FOS: Philosophy, ethics and religion, World Wide Web, Philosophy, 13. Climate action, Computer Science, Physical Sciences, Political Science and International Relations, FOS: Languages and literature, Law

Handling of Personal Data by Smart Home Equipment: an Exploratory Analysis in the Context of LGPD

Συγγραφείς: Thiago Adriano Coleti, Renato Balancieri, André Menolli, Omar Ali Mahmoud, Victor Hugo Sotti, Michel Marialva Yvano, Marcelo Morandini

Πηγή: Journal on Interactive Systems, Vol 15, Iss 1 (2024)

Θεματικοί όροι: Smart Home, Computer engineering. Computer hardware, Sociology and Political Science, Social Sciences, 02 engineering and technology, 7. Clean energy, Privacy and Security, Data science, TK7885-7895, QA76.75-76.765, Context (archaeology), Exploratory data analysis, Artificial Intelligence, Personal Data, 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, Computer software, Data mining, 2. Zero hunger, Geography, 05 social sciences, Privacy-Preserving Techniques for Data Analysis and Machine Learning, 1. No poverty, 16. Peace & justice, Computer science, Exploratory analysis, Archaeology, Computer Science, Physical Sciences, 0503 education, Internet Users' Information Privacy Concerns, General Data Protection Regulation

Σύνδεσμος πρόσβασης: https://doaj.org/article/e26728363be642bb8b95cf7a660e598c

SHAPER: A General Architecture for Privacy-Preserving Primitives in Secure Machine Learning

Συγγραφείς: Ziyuan Liang, Qin Jin, Zhiyong Wang, Zhaohui Chen, Zhaoquan Gu, Yun-Ju Lu, Fan Zhang

Πηγή: Transactions on Cryptographic Hardware and Embedded Systems, Vol 2024, Iss 2 (2024)

Θεματικοί όροι: FOS: Computer and information sciences, Secure Multi-party Computation, Computer engineering. Computer hardware, Artificial intelligence, Information technology, Privacy-Preserving Machine Learning, Security Challenges in Cloud Computing, 7. Clean energy, Searchable Encryption, Visual arts, TK7885-7895, Artificial Intelligence, Computer security, Architecture, Secure Computation, Human–computer interaction, Advanced Cryptographic Schemes and Protocols, Multi-Party Computation, Privacy-Preserving Techniques for Data Analysis and Machine Learning, Additive Homomorphic Encryption, Hardware Accelerator, T58.5-58.64, Computer science, Computer Science, Physical Sciences, Privacy-Preserving Computation, Homomorphic Encryption, FOS: Civil engineering, Art, Information Systems

Σύνδεσμος πρόσβασης: https://doaj.org/article/1a0d06d407194293903d7dae54231b8c

Federated learning enables 6 G communication technology: Requirements, applications, and integrated with intelligence framework

Συγγραφείς: Mohammad Kamrul Hasan, Arslan Habib, Shayla Islam, Nurhizam Safie, Taher M. Ghazal, Muhammad Attique Khan, Ahmed Ibrahim Alzahrani, Nasser Alalwan, Seifedine Kadry, Anum Masood

Πηγή: Alexandria Engineering Journal, Vol 91, Iss, Pp 658-668 (2024)

Θεματικοί όροι: Communication technology, Advanced Cryptographic Schemes and Protocols, Integrated learning, Knowledge management, Privacy-Preserving Techniques for Data Analysis and Machine Learning, Engineering (General). Civil engineering (General), Intelligent Reflecting Surfaces in Wireless Communications, Computer science, 7. Clean energy, 6G Networks, Systems engineering, Federate Learning, Engineering, Artificial Intelligence, Electrical engineering, Machine learning, Computer Science, Physical Sciences, FOS: Electrical engineering, electronic engineering, information engineering, TA1-2040, Electrical and Electronic Engineering, Electronics, Federated Learning, 6G

Σύνδεσμος πρόσβασης: https://doaj.org/article/43c8b33408f249f985400c9cb408a2e0

FedDCT: Federated Learning of Large Convolutional Neural Networks on Resource-Constrained Devices Using Divide and Collaborative Training

Συγγραφείς: Quan Dong Nguyen, Hieu H. Pham, Kok‐Seng Wong, Phi Le Nguyen, Truong Thao Nguyen, N. Minh

Πηγή: IEEE Transactions on Network and Service Management. 21:418-436

Θεματικοί όροι: Artificial neural network, FOS: Computer and information sciences, Artificial intelligence, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, Convolutional neural network, 02 engineering and technology, Edge device, Bottleneck, Deep Learning, Artificial Intelligence, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, Cloud computing, Optimization Methods in Machine Learning, Embedded system, Privacy-Preserving Techniques for Data Analysis and Machine Learning, Deep learning, Computer science, Distributed computing, Process (computing), Overhead (engineering), Operating system, Computer Science, Physical Sciences, Federated Learning

Σύνδεσμος πρόσβασης: http://arxiv.org/abs/2211.10948

A Probabilistic Approach for Missing Data Imputation

Συγγραφείς: Muhammed Nazmul Arefin, Abdul Kadar Muhammad Masum

Πηγή: Complexity, Vol 2024 (2024)

Θεματικοί όροι: Statistics and Probability, Artificial intelligence, Missing data, 0206 medical engineering, Privacy-Preserving Techniques for Data Analysis and Machine Learning, Multiple Imputation, QA75.5-76.95, 02 engineering and technology, Regularization and Variable Selection Methods, Computer science, Big data, Methods for Handling Missing Data in Statistical Analysis, Artificial Intelligence, Electronic computers. Computer science, Computer Science, Physical Sciences, Machine learning, 8. Economic growth, 0202 electrical engineering, electronic engineering, information engineering, FOS: Mathematics, Imputation (statistics), Data mining, Mathematics, Probabilistic logic

Περιγραφή αρχείου: text/xhtml

Σύνδεσμος πρόσβασης: https://doaj.org/article/6dca6583d7f840dc9ac8aed70ac23714

An Improved and Efficient Coercion-resistant Measure for Electronic Voting System

Συγγραφείς: Tzer‐Long Chen, Chia‐Hui Liu, Ya-Hui Ou, Yao-Min Huang, Zhen-Yu Wu

Πηγή: International Journal of Information Security. 23:2637-2654

Θεματικοί όροι: Secure Multi-party Computation, FOS: Political science, FOS: Law, 02 engineering and technology, 7. Clean energy, Artificial Intelligence, Computer security, Bullet voting, 0202 electrical engineering, electronic engineering, information engineering, Business, Coercion (linguistics), Political science, Order (exchange), Secure Computation, Advanced Cryptographic Schemes and Protocols, Electronic voting, Politics, Privacy-Preserving Techniques for Data Analysis and Machine Learning, Linguistics, Volition (linguistics), 16. Peace & justice, Computer science, Cardinal voting systems, FOS: Philosophy, ethics and religion, Philosophy, Machine Learning for Internet Traffic Classification, E-Voting, Computer Science, Physical Sciences, Cryptography, FOS: Languages and literature, Internet privacy, Voting, Law, Finance

Fortifying Federated Learning in IIoT: Leveraging Blockchain and Digital Twin Innovations for Enhanced Security and Resilience

Συγγραφείς: Prathiba, SB, Govindarajan, Y, Pranav Amirtha Ganesan, V, Ramachandran, A, Selvaraj, AK, Bashir, AK, Reddy Gadekallu, T

Πηγή: IEEE Access, Vol 12, Pp 68968-68980 (2024)

Θεματικοί όροι: FOS: Computer and information sciences, 7. Clean energy, 09 Engineering, data poisoning, Blockchain, Artificial Intelligence, Computer security, 10 Technology, digital twin, Secure Computation, 9. Industry and infrastructure, Physics, 4. Education, Privacy-Preserving Techniques for Data Analysis and Machine Learning, Blockchain and Internet of Things Integration, decentralized federated learning, 16. Peace & justice, Computer science, TK1-9971, Resilience (materials science), Computer Science, Physical Sciences, Thermodynamics, model poisoning, 08 Information and Computing Sciences, Electrical engineering. Electronics. Nuclear engineering, industrial internet of things, Federated Learning, Information Systems

Σύνδεσμος πρόσβασης: https://doaj.org/article/402846f923ec4a1799b5ab59ab5eafe2
https://e-space.mmu.ac.uk/635089/

MAPLE: MArkov Process Leakage attacks on Encrypted Search

Συγγραφείς: Seny Kamara, Abdelkarim Kati, Tarik Moataz, Jamie DeMaria, Andrew Park, Amos Treiber

Πηγή: Proceedings on Privacy Enhancing Technologies. 2024:430-446

Θεματικοί όροι: Economics, Markov chain, Macroeconomics, Encryption, 02 engineering and technology, Leverage (statistics), Searchable Encryption, Theoretical computer science, Artificial Intelligence, Computer security, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, Attribute-Based Encryption, Data mining, Secure Computation, Advanced Cryptographic Schemes and Protocols, Privacy-Preserving Techniques for Data Analysis and Machine Learning, Computer science, Information leakage, Leakage (economics), Machine Learning for Internet Traffic Classification, Computer Science, Physical Sciences, Hash function, Cryptography, Encrypted Traffic, Homomorphic Encryption

Privacy Preserving Inference for Deep Neural Networks: Optimizing Homomorphic Encryption for Efficient and Secure Classification

Συγγραφείς: Aftab Akram, Fawad Khan, Shahzaib Tahir, Asif Iqbal, Syed Aziz Shah, Abdullah Baz

Πηγή: IEEE Access, Vol 12, Pp 15684-15695 (2024)

Θεματικοί όροι: Artificial neural network, Artificial intelligence, Information privacy, Combinatorial Optimization and Complexity Theory, homomorphic encryption, Encryption, Convolutional neural network, cloud server, MNIST database, Inference, Artificial Intelligence, Computer security, Machine learning, Cloud computing, activation function, Differential Privacy, Data mining, Secure Computation, Privacy Preservation, Advanced Cryptographic Schemes and Protocols, Privacy-Preserving Techniques for Data Analysis and Machine Learning, security and privacy, approximation techniques, 16. Peace & justice, Computer science, Homomorphic encryption, TK1-9971, Operating system, Computational Theory and Mathematics, Computer Science, Physical Sciences, Electrical engineering. Electronics. Nuclear engineering, Privacy-Preserving Computation, Homomorphic Encryption

Σύνδεσμος πρόσβασης: https://doaj.org/article/503e72ca482f4492baa13e4ac604e156

Exploring the potential of federated learning in mental health research: a systematic literature review: a systematic literature review

Συγγραφείς: Samar Samir Khalil, Noha S. Tawfik, Marco Spruit

Πηγή: Applied Intelligence. 54:1619-1636

Θεματικοί όροι: Pooling, Artificial intelligence, Economics, Federated learning, Health Informatics, Mathematical analysis, 7. Clean energy, Data science, Artificial Intelligence, Computer security, Health Sciences, Machine learning, FOS: Mathematics, Pathology, Raw data, 10. No inequality, Economic growth, Artificial Intelligence in Medicine, Psychiatry, Domain (mathematical analysis), Human–computer interaction, Deep Learning Applications in Healthcare, Privacy-Preserving Techniques for Data Analysis and Machine Learning, Medical diagnosis, Health care, Medical Concept Embedding, Computer science, Programming language, 3. Good health, Mental illness, Computer Science, Physical Sciences, Medicine, Mental health, Federated Learning, Mathematics

Περιγραφή αρχείου: application/pdf

Σύνδεσμος πρόσβασης: https://hdl.handle.net/1887/4197237
https://hdl.handle.net/1887/4038333

Quantum-empowered federated learning and 6G wireless networks for IoT security: Concept, challenges and future directions

Συγγραφείς: Danish Javeed, Muhammad Shahid Saeed, Ijaz Ahmad, Muhammad Adil, Prabhat Kumar, A.K.M. Najmul Islam

Πηγή: Future Generation Computer Systems. 160:577-597

Θεματικοί όροι: Computer network, Computer Networks and Communications, Physics, Internet of Things, Privacy-Preserving Techniques for Data Analysis and Machine Learning, Computer science, Quantum mechanics, 7. Clean energy, Quantum, IoT Devices, Cooperative Diversity in Wireless Networks, Artificial Intelligence, Machine Learning for Internet Traffic Classification, Computer security, Computer Science, Physical Sciences, Wireless, Telecommunications, Federated Learning, Wireless network, Secure Computation

A novel privacy-aware global infrastructure for ecological footprint calculator based on the Internet of things and blockchain

Συγγραφείς: Nadim Elsakaan, Kamal Amroun

Πηγή: The Journal of Supercomputing. 80:9494-9531

Θεματικοί όροι: FOS: Computer and information sciences, Internet of Things, Immutability, 7. Clean energy, 12. Responsible consumption, Blockchain, Server, Artificial Intelligence, Computer security, 11. Sustainability, Ecological footprint, Biology, 2. Zero hunger, Ecology, 9. Industry and infrastructure, Blockchain and Internet of Things Integration, Privacy-Preserving Techniques for Data Analysis and Machine Learning, 16. Peace & justice, Computer science, World Wide Web, Sustainability, 13. Climate action, FOS: Biological sciences, Computer Science, Physical Sciences, 8. Economic growth, The Internet, Information Systems

Self-Organizing Democratized Learning: Toward Large-Scale Distributed Learning Systems

Συγγραφείς: Minh N. H. Nguyen, Shashi Raj Pandey, Tri Nguyen Dang, Eui‐Nam Huh, Nguyen H. Tran, Walid Saad, Choong Seon Hong

Πηγή: Nguyen, M N H, Pandey, S R, Dang, T N, Huh, E-N, Tran, N H, Saad, W & Hong, C S 2023, 'Self-Organizing Democratized Learning : Toward Large-Scale Distributed Learning Systems', IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 12, pp. 10698-10710. https://doi.org/10.1109/TNNLS.2022.3170872
Nguyen, M N H, Pandey, S R, Dang, T N, Huh, E-N, Tran, N H, Saad, W & Hong, C S 2023, ' Self-Organizing Democratized Learning : Toward Large-Scale Distributed Learning Systems ', IEEE Transactions on Neural Networks and Learning Systems . https://doi.org/10.1109/TNNLS.2022.3170872

Θεματικοί όροι: FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial intelligence, Generalization, FOS: Mechanical engineering, Machine Learning (stat.ML), MNIST database, Participatory Sensing, Unsupervised learning, Mathematical analysis, Machine Learning (cs.LG), Engineering, Theoretical computer science, Philosophical considerations, Statistics - Machine Learning, Artificial Intelligence, Self-Reconfigurable Robotic Systems and Modular Robotics, Machine learning, FOS: Mathematics, distributed artificial intelligences (AIs), Distance learning, Learning systems, 9. Industry and infrastructure, Mechanical Engineering, Privacy-Preserving Techniques for Data Analysis and Machine Learning, Distributed Control, Computational modeling, Democratized learning, Deep learning, Crowdsourcing for Research and Data Collection, 16. Peace & justice, self-organization, Computer science, Computer Science Applications, Computer aided instruction, Task analysis, Computer Science, Physical Sciences, hierarchical learning, Federated Learning, Mathematics

Περιγραφή αρχείου: application/pdf

Σύνδεσμος πρόσβασης: https://pubmed.ncbi.nlm.nih.gov/35536803
http://arxiv.org/abs/2007.03278
http://www.scopus.com/inward/record.url?scp=85132540104&partnerID=8YFLogxK
https://vbn.aau.dk/ws/files/698876079/Self-Organizing_Democratized_Learning_Toward_Large-Scale_Distributed_Learning_Systems.pdf
https://doi.org/10.1109/TNNLS.2022.3170872
https://vbn.aau.dk/da/publications/fd0271f3-0474-4ce5-86ec-fcf7348a90ef
https://vbn.aau.dk/da/publications/312a1b6d-ee50-4cfe-9952-e863be7b19c9
https://vbn.aau.dk/en/publications/fd0271f3-0474-4ce5-86ec-fcf7348a90ef
https://doi.org/10.1109/TNNLS.2022.3170872
http://hdl.handle.net/10919/110774
https://doi.org/10.1109/TNNLS.2022.3170872

A Privacy-Preserving Federated Learning Framework for Blockchain Networks

Συγγραφείς: Youssif Abuzied, Mohamed Ghanem, Fadi Dawoud, Habiba Gamal, Eslam Soliman, Hossam Sharara, Tamer ElBatt

Πηγή: Cluster Computing. 27:3997-4014

Θεματικοί όροι: FOS: Computer and information sciences, Computer network, Advanced Cryptographic Schemes and Protocols, 9. Industry and infrastructure, 4. Education, Privacy-Preserving Techniques for Data Analysis and Machine Learning, Blockchain and Internet of Things Integration, Federated learning, Lattice-based Cryptography, 02 engineering and technology, Computer science, 7. Clean energy, Searchable Encryption, Distributed computing, Blockchain, Artificial Intelligence, Computer security, Computer Science, Physical Sciences, 0202 electrical engineering, electronic engineering, information engineering, Privacy-Preserving Computation, 10. No inequality, Federated Learning, Information Systems

5 G and beyond wireless network optimization through RIS technology: a pricing game

Συγγραφείς: Lhoussaine Daoudi, Mohamed Baslam, Mohamed Zagour, Saïd Safi

Πηγή: Cluster Computing. 27:5867-5877

Θεματικοί όροι: Artificial intelligence, Economics, FOS: Political science, FOS: Law, Operations research, Cournot competition, Rationality, 7. Clean energy, Nash equilibrium, 12. Responsible consumption, Engineering, Artificial Intelligence, Machine learning, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Mathematics, Base station, Reconfigurable Intelligent Surfaces, Electrical and Electronic Engineering, Stability (learning theory), Political science, Game theory, Smart Radio Environments, 2. Zero hunger, Computer network, Mathematical economics, 9. Industry and infrastructure, Bounded rationality, Mathematical optimization, Privacy-Preserving Techniques for Data Analysis and Machine Learning, 1. No poverty, Intelligent Reflecting Surfaces in Wireless Communications, Computer science, Duopoly, Physical Sciences, Computer Science, 8. Economic growth, Wireless, Telecommunications, Law, Mathematics

Advancing Pandemic Preparedness in Healthcare 5.0: A Survey of Federated Learning Applications

Συγγραφείς: Saeed Hamood Alsamhi, Ammar Hawbani, Alexey V. Shvetsov, Santosh Kumar

Πηγή: Advances in Human-Computer Interaction, Vol 2023 (2023)

Θεματικοί όροι: FOS: Computer and information sciences, Radiology, Nuclear Medicine and Imaging, Preparedness, Knowledge management, FOS: Political science, Transformative learning, FOS: Law, 02 engineering and technology, Infectious disease (medical specialty), Role of Digital Technologies in Pandemic Contact Tracing, 03 medical and health sciences, 0302 clinical medicine, Context (archaeology), Artificial Intelligence, Health Sciences, 0202 electrical engineering, electronic engineering, information engineering, Pathology, Psychology, Business, Disease, Political science, Biology, Pandemic, Pedagogy, Privacy-Preserving Techniques for Data Analysis and Machine Learning, Health care, Paleontology, QA75.5-76.95, Applications of Deep Learning in Medical Imaging, Computer science, 3. Good health, Coronavirus disease 2019 (COVID-19), FOS: Psychology, Electronic computers. Computer science, Computer Science, Physical Sciences, Medicine, Federated Learning, Law, Information Systems

Περιγραφή αρχείου: text/xhtml

Σύνδεσμος πρόσβασης: https://doaj.org/article/1da54570f165421cbe21725917a7e27f

Optimized federated learning based on Adagrad algorithm and algorithm optimization

Συγγραφείς: Eric King‐wah Chu, Dengbo Li, Yangfan Tong

Πηγή: Applied and Computational Engineering. 19:9-17

Θεματικοί όροι: FOS: Computer and information sciences, Artificial neural network, Artificial intelligence, Gradient descent, 4. Education, Mathematical optimization, Privacy-Preserving Techniques for Data Analysis and Machine Learning, Digital Image Processing and Artificial Neural Networks, Federated learning, 15. Life on land, Computer science, 7. Clean energy, Algorithm, Optimization algorithm, Artificial Intelligence, Computer Science, Physical Sciences, Machine learning, FOS: Mathematics, Data Mining in Various Applications, Federated Learning, Mathematics, Information Systems