• Please read through all the templates before choosing • Pick the most relevant text template(s) from the following page and delete all others. • Edit the text as necessary, ensuring that the original incorrect text is included for the record, please see the below. • Please do not use any extra formatting when editing...
Mini Han Wang, Norberto Peporine Lopes, Nuno S. Osório· Frontiers in Artificial Inte...· 0 citations
This study presents a reproducible proof of concept and a practical baseline for a secure machine learning approach for healthcare collaborations and demonstrates a reproducible proof of concept and a practical baseline for a secure machine learning approach for healthcare collaborations.
Fardin Muttaki, Aqeel Sahi, Shahab A. Abdulla· Journal of Cybersecurity and...· 0 citations
This paper presents a novel approach to differential privacy in federated learning, termed Dynamic Differential Privacy (DDP). The core idea is to adapt the privacy budget dynamically, responding to the varying sensitivity of local data. Traditional federated learning frequently utilizes a static privacy budget, which...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Federated learning (FL) offers a promising approach to training machine learning models on decentralized data sources without direct data sharing. However, traditional FL methods are vulnerable to information leakage and model divergence, particularly when dealing with highly heterogeneous client datasets. This researc...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Reach audiences
Advertise in front of researchers, engineers, and readers.
Findings demonstrate that the proposed framework provides an accurate, privacy-aware, and interpretable solution for decentralized CKD prediction, and maintains robust performance under Gaussian noise.
Komal Kumar Napa, D. Sathyanarayanan, Raguraman Purushothaman et al.· Discover Artificial Intellig...· 0 citations
"This dataset contains the source code and evaluation logs supporting the manuscript \"FedWave: Stealthy Wavelet-Domain Backdoor Attacks in Federated Learning,\" submitted to the IEEE Transactions on Information Forensics and Security.FedWave is an anchor-aligned wavelet-subband backdoor framework for federated learnin...
Xin Ai, Yang Cao, Mengli Wei· IEEE DataPort· 0 citations
A conceptual framework is proposed to illustrate the integration of customer behavioral characteristics, policy attributes, and advanced machine learning models into an intelligent decision-support system for claim prediction, highlighting the importance of explainable AI, continuous model monitoring, and human-in-the-...
Pragadeesh Roopchander· International Journal of Cre...· 0 citations
This paper proposes a novel approach to decentralized federated learning (DFL) that leverages secure multi-party computation (SMPC) to guarantee data privacy during collaborative model training. Traditional federated learning methods, while promoting data sharing for model improvement, inherently expose individual data...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
This paper proposes a novel approach to decentralized federated learning (DFL) that incorporates Byzantine fault tolerance (BFT) using blockchain consensus. Traditional DFL systems are vulnerable to malicious clients injecting poisoned model updates, compromising the overall model accuracy and data integrity. Our syste...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Blockchain consensus still forces a hard choice among scalability, security, and energy use. Redbelly, a leaderless Byzantine Fault Tolerance protocol, largely settles the scalability-versus-energy side of that tension, yet it accepts any cryptographically valid transaction without judging whether it is economically fr...
The heterogeneity of data across Industrial Internet of Things (IIoT) devices poses significant challenges to federated learning-based intrusion detection systems, where the Non-IID data distribution leads to poor detection performance, particularly on rare attack classes. To address these issues, this letter proposes...
Xiaofei Huang, Fei Shu, Jaydar Jingus et al.· 0 citations
"This dataset contains Ultra-Wideband (UWB) ranging and localization measurements collected for the evaluation of adaptive and federated learning methods for indoor positioning in challenging environments. The data were acquired in a controlled two-room laboratory deployment designed to capture realistic line-of-sight...
Christos Sad, Kostas Siozios· IEEE DataPort· 0 citations
Prabha Jha used her experience with MIT Open Learning’s program for senior executives to develop AI solutions for her employer, Verizon, and to write a book.
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
