Federated learning for intrusion detection in IoT environments: a privacy-preserving strategy by Ansam Khraisat, Ammar Alazab, Moutaz Alazab, Areej Obeidat, Sarabjot Singh, Tony Jan

“…While allowing devices to benefit from the network’s collective insights, this decentralised learning methodology safeguards data privacy. Using a real-world IoT dataset and two popular federated learning algorithms—Federated Average and Federated Average with Momentum—the study assesses the effectiveness of PEIoT-DS. …”
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Classification auditting scheme for privacy protection of outsourced EHR based on distributed storage by ZHANG Xiaoxu, CHEN Yuchen, HA Guanxiong, JIA Chunfu

“…EHR contains a large amount of private information, however, data outsourcing can create security risks, potentially compromising the integrity and privacy of EHR. …”
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Classification auditting scheme for privacy protection of outsourced EHR based on distributed storage by ZHANG Xiaoxu, CHEN Yuchen, HA Guanxiong, JIA Chunfu

“…EHR contains a large amount of private information, however, data outsourcing can create security risks, potentially compromising the integrity and privacy of EHR. …”
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Navigating ethics in HIV data and biomaterial management within Black, African, and Caribbean communities in Canada by Rusty Souleymanov, Bolaji Akinyele-Akanbi, Chinyere Njeze, Patricia Ukoli, Paula Migliardi, Linda Larcombe, Gayle Restall, Laurie Ringaert, Michael Payne, John Kim, Wangari Tharao, Ayn Wilcox

“…The study employed iterative inductive thematic data analysis. Findings Participants expressed significant concerns about the collection, sharing, and use of HIV data from healthcare encounters, revealing mistrust towards institutions like police, child welfare, and immigration accessing their health information. …”
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Blockchain-Based Privacy-Preserving Authentication and Access Control Model for E-Health Users by Abdullah Alabdulatif

“…The advancement of e-health systems has resulted in substantial enhancements in healthcare delivery via effective data management and accessibility. The use of digital health solutions presents dangers to sensitive health information, including unauthorised access, privacy violations, and security weaknesses. …”
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Privacy‐preserving speaker verification system based on binary I‐vectors by Aymen Mtibaa, Dijana Petrovska‐Delacrétaz, Jérôme Boudy, Ahmed Ben Hamida

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Board of Directors Role in Data Privacy Governance: Making the Transition from Compliance Driven to Good Business Stewardship by David Warner, Lisa McKee

“…Data collection, use, leveraging, and sharing as a business practice and advantage has proliferated over the past decade. …”
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Heap Bucketization Anonymity—An Efficient Privacy-Preserving Data Publishing Model for Multiple Sensitive Attributes by J. Jayapradha, M. Prakash, Youseef Alotaibi, Osamah Ibrahim Khalaf, Saleh Ahmed Alghamdi

“…Currently, significant focus has been established to protect privacy during data publishing. The existing privacy models for multiple sensitive attributes do not concentrate on the correlation among the attributes, which in turn leads to much utility loss. …”
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Sensitive data donation in practice: unforeseen challenges and lessons learned by Alejandra Gómez Ortega

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Efficient Traceability Systems with Smart Contracts: Balancing On-Chain and Off-Chain Data Storage for Enhanced Scalability and Privacy by Manuel José Fernández-Iglesias, Christian Delgado von Eitzen, Luis Anido-Rifón

“…We discuss the advantages of using blockchain technology to notarise traceability activities, ensuring immutability and transparency by exploring two main scenarios, namely one where hash keys (i.e, cryptographic digests) are stored on-chain while detailed data remain off-chain, and another where all traceability data are fully stored on-chain. …”
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An online tool based on the Internet of Things and intelligent blockchain technology for data privacy and security in rural and agricultural development by Krishnaprasath Vellimalaipattinam Thiruvenkatasamy, Hayder M. A. Ghanimi, Sudhakar Sengan, Meshal Ghalib Alharbi

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An enhanced dynamic KC-slice model for privacy preserving data publishing with multiple sensitive attributes by inducing sensitivity by N.V.S. Lakshmipathi Raju, M.N. Seetaramanath, P. Srinivasa Rao

“…Privacy Preserving Data Publishing (PPDP) is an important aspect of real world scenarios. …”
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Distributed cross-learning for equitable federated models - privacy-preserving prediction on data from five California hospitals by Tsung-Ting Kuo, Rodney A. Gabriel, Jejo Koola, Robert T. Schooley, Lucila Ohno-Machado

“…We compared D-CLEF with centralized/siloed/federated learning in horizontal or vertical scenarios. Using data of more than 15,000 patients with COVID-19 from five University of California (UC) Health medical centers, surgical data from UC San Diego, and heart disease data from Edinburgh, UK, D-CLEF performed close to the centralized solution, outperforming the siloed ones, and equivalent to the federated learning counterparts, but with increased synchronization time. …”
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Exploring the Use of AI in Qualitative Data Analysis: Comparing Manual Processing with Avidnote for Theme Generation by S. M. Akramul Kabir, Fareeha Ali, Rana Lotfy Ahmed, Ruqayya Sulaiman-Hill

“…However, fundamental concerns persist regarding the robustness, generalisability, credibility, reliability and trustworthiness of qualitative research when using AI technologies. Ethical considerations, such as data security and privacy, also need to be addressed in research settings. …”
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Design of an efficient dynamic context‐based privacy policy deployment model via dual bioinspired Q learning optimisations by Namrata Jiten Patel, Ashish Jadhav

“…The combination of ALO, FFO, and Q‐learning techniques offers a practical solution to evolving data privacy challenges and enhances flexibility in various use case scenarios.…”
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Federated intelligence for smart grids: a comprehensive review of security and privacy strategies by Raseel Z. Alshamasi, Dina M. Ibrahim

“…The paper highlights critical gaps and outlines future research directions for improving smart grid resilience using federated intelligence.…”
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Enhancing Privacy While Preserving Context in Text Transformations by Large Language Models by Tymon Lesław Żarski, Artur Janicki

“…Despite the convenience, many users are unaware of the risks posed to their sensitive and personal data. This study addresses this issue by presenting a comprehensive solution to prevent personal data leakage using online tools. …”
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The method for approximate continuous Skyline query based on privacy protection in road network by Song Li, Xiaolong Yang, Liping Zhang, Guanglu Sun

“…Abstract Existing road network continuous Skyline queries often neglect user location privacy and data privacy protection. This paper proposes a method for Approximate Continuous Skyline Query with Privacy Protection in road network (ACPP) environments to address these issues. …”
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Analysis of Processing Accidents due to H2S in Clot Stuck Unit of one of the South Pars Refineries Leakage Using Determination of Safe Privacy Approach by M Ebrahemzadih, Farshad Foroghi nasab, M Mortazavi, R Soltani gerdefaramarzi

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Time Series Classification Using Federated Convolutional Neural Networks and Image-Based Representations by Felipe A. R. Silva, Omid Orang, Fabricio Javier Erazo-Costa, Petronio C. L. Silva, Pedro H. Barros, Ricardo P. M. Ferreira, Frederico Gadelha Guimaraes

“…Federated Learning (FL) enables collaborative training across distributed clients while ensuring data privacy. The method’s effectiveness is evaluated using 40 datasets from the UCR Archive. …”
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