Federated learning framework for IoT intrusion detection using tab transformer and nature-inspired hyperparameter optimization by Mohamed Abd Elaziz, Mohamed Abd Elaziz, Mohamed Abd Elaziz, Ibrahim A. Fares, Abdelghani Dahou, Mansour Shrahili

“…The goal of the developed framework is to improve the detection of IDS without using centralized data to preserve privacy. Whereas it enhances the processing and detection capability of huge amounts of data generated from IoT devices. …”
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Shopping Data for Population Health Surveillance: Opportunities, Challenges, and Future Directions by Alisha Suhag, Romana Burgess, Anya Skatova

“…This paper explores the potential of loyalty card data to strengthen public health surveillance across 4 key behavioral risk domains: diet, alcohol, tobacco, and over-the-counter medication use. …”
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SHARE: An ethical framework for equitable data sharing in Caribbean health research by Michael H. Campbell, Natalie S. Greaves

“…Using the SHARE framework can support regionally relevant and culturally responsive work already underway in the region and further develop capacity for intentional sharing and (re)use of Caribbean health data.…”
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Blockchain and NFT-Based Solution for Genomic Data Management, Sharing, and Monetization by Ahmad Musamih, Khaled Salah, Raja Jayaraman, Samer Ellaham, Mohammed Omar, Ibrar Yaqoob

“…In this paper, we propose a blockchain and NFT-based solution that addresses the challenges of managing, sharing, and monetizing genomic data while preserving privacy using Threshold Cryptography and Fully Homomorphic Encryption (FHE). …”
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An Artificial Intelligence Pipeline for Hepatocellular Carcinoma: From Data to Treatment Recommendations by Zhang X, Yang L, Liu C, Yuan X, Zhang Y

“…However, challenges such as data quality, standardization, and privacy remain. …”
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Generating and evaluating synthetic data in digital pathology through diffusion models by Matteo Pozzi, Shahryar Noei, Erich Robbi, Luca Cima, Monica Moroni, Enrico Munari, Evelin Torresani, Giuseppe Jurman

“…Abstract Synthetic data is becoming a valuable tool for computational pathologists, aiding in tasks like data augmentation and addressing data scarcity and privacy. …”
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Trusted access control mechanism for data with blockchain-assisted attribute encryption by Chang Liu, Dong Wang, Da Li, Shaoyong Guo, Wenjing Li, Xuesong Qiu

“…Ciphertext policy attribute-based encryption (CP-ABE) model is widely used in cloud data sharing scenarios, but there are problems such as privacy leakage of access policy, irrevocability of user or attribute, key escrow, and trust bottleneck. …”
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Efficient unpaired data validation and aggregation protocol in industrial Internet of things by MA Rong, FENG Tao

“…Within the context of an IIoT environment based on elliptic curve cryptography, homomorphic encryption was emploied to safeguard data privacy and a verification key management scheme was introduced, facilitating secure and efficient unpaired verification. …”
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Big IoT Data Analytics: Architecture, Opportunities, and Open Research Challenges by Mohsen Marjani, Fariza Nasaruddin, Abdullah Gani, Ahmad Karim, Ibrahim Abaker Targio Hashem, Aisha Siddiqa, Ibrar Yaqoob

“…However, such data are not useful without analytic power. Numerous big data, IoT, and analytics solutions have enabled people to obtain valuable insight into large data generated by IoT devices. …”
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A Web-Based Application for Smart City Data Analysis and Visualization by Panagiotis Karampakakis, Despoina Ioakeimidou, Periklis Chatzimisios, Konstantinos A. Tsintotas

“…Smart cities are urban areas that use contemporary technology to improve citizens’ overall quality of life. …”
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A COMPREHENSIVE REVIEW OF GENERATIVE ARTIFICIAL INTELLIGENCE APPLICATIONS IN DATA VISUALIZATION by Luong Thi Minh Hue*, Nguyen The Vinh, Nguyen Van Viet, Nguyen Huu Khanh, Nguyen Kim Son, Duong Thuy Huong

“…Using natural language to generate visual representations of data (NL2VIS) is emerging as a promising research direction, driven by the rapid development of Generative AI (GenAI). …”
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PCR and Bio-signature for data confidentiality and integrity in mobile cloud computing by Sreeja Cherillath Sukumaran, Mohammed Misbahuddin

“…Mobile Cloud Computing (MCC) allows users more possibilities to access services conveniently. But data security and privacy issues still act as barriers for adoption to cloud technology when dealing with confidential data. …”
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A Remedy for Heterogeneous Data: Clustered Federated Learning with Gradient Trajectory by Ruiqi Liu, Songcan Yu, Linsi Lan, Junbo Wang, Krishna Kant, Neville Calleja

“…Federated Learning (FL) has recently attracted a lot of attention due to its ability to train a machine learning model using data from multiple clients without divulging their privacy. …”
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FedDB: A Federated Learning Approach Using DBSCAN for DDoS Attack Detection by Yi-Chen Lee, Wei-Che Chien, Yao-Chung Chang

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Decentralized Infrastructure for Digital Notarizing, Signing, and Sharing Documents Securely Using Microservices and Blockchain by Irimia Cosmin-Iulian, Iftene Adrian

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Securing the metaverse: Machine learning–based perspectives on risk, trust, and governance by Krishnashree Achuthan, Sasangan Ramanathan, Raghu Raman

“…The rapid expansion of the metaverse presents significant cybersecurity and privacy challenges, requiring structured, data-driven analysis. …”
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The algorithmic consumer: A conceptual investigation of AI’s influence on consumer preferences and decisions by Annur Islam Sifat

“…By a thorough literature review and commentary, I critically analyzed the impact of AI’s personalization algorithm and addressed ethical implications in terms of potential bias, data privacy, and transparency. This paper establishes a conceptual framework to illustrate how AI technologies, including machine learning, natural language processing, and predictive analytics, intersect with facets of consumer psychology, allowing for personalization of experiences, market segmentation, and influencing behaviour in real time. …”
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Diabetes: Non-Invasive Blood Glucose Monitoring Using Federated Learning with Biosensor Signals by Narmatha Chellamani, Saleh Ali Albelwi, Manimurugan Shanmuganathan, Palanisamy Amirthalingam, Anand Paul

“…To address these challenges, this study proposes a federated learning (FL)-based solution that enables multiple healthcare organizations to collaboratively train a global model without sharing raw patient data, thereby enhancing model performance while ensuring data privacy and security. …”
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Mitigating Sinkhole Attacks in MANET Routing Protocols using Federated Learning HDBNCNN Algorithm by Sherril Sophie Maria Vincent

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Lithium-Ion Battery State of Health Degradation Prediction Using Deep Learning Approaches by Talal Alharbi, Muhammad Umair, Abdulelah Alharbi

“…Traditional centralized deep learning models have shown promising results, but they raise concerns related to data privacy, as data needed to be collected and trained on a single node. …”
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