federated learning

Human-Centered AI and Decision Support in Security Operations Centers

The growing complexity of cyber threats has made Security Operations Centers (SOCs) essential for real-time threat detection, incident response, and infrastructure protection. However, traditional black-box AI models often reduce trust and transparency in cybersecurity decisions. This chapter explores human-centered Ex...

D3MI: an efficient and powerful federated imputation method for bias reduction in the analysis of distributed incomplete data by accounting for within-site correlation and between-site heterogeneity

BACKGROUND: Electronic health records (EHRs) collected from diverse healthcare institutions offer a rich and representative data source for clinical research. Federated learning enables analysis of these distributed data without sharing sensitive patient-level information, preserving privacy. However, missing data rema...

Retrieval-Augmented Generation Applications and Development in the Field of Electronic Test Instruments

The rapid development of artificial intelligence (AI), especially the fast iteration and widespread deployment of large language models (LLMs), has ushered in a new paradigm for the intelligent augmentation of electronic test instruments and automatic test systems (ATS). By combining the powerful reasoning and generati...

Federated Learning in the Era of Large Models: Core Challenges, Representative Solutions, and Emerging Directions

With the rapid advancement of the Internet and the emergence and popularity of large language models, the demands for high-quality data, communication capacity and security and privacy have increased significantly. However, a large amount of data is distributed across different devices, and cannot be collected legally...

Intelligent Technologies as Proponents of Global Development and Sustainability: An Approach Based on India's Digital Infrastructure

The seventeen core goals of the UN's 2030 Agenda for Sustainable Development demand the need for collective action along social, economic, and environmental fronts. Artificial intelligence (AI), the Internet of Things (IoT), blockchain, along with cloud/edge computing are notable examples of intelligent technologies an...

Diagnostic Performance of Deep Learning Models for Ocular Toxoplasmosis Using Fundus Photography: A Systematic Review and Meta-Analysis.

BACKGROUND Ocular toxoplasmosis (OT) is the leading infectious cause of posterior uveitis worldwide, yet diagnosis remains challenging without a universal gold standard. Although deep learning (DL) shows significant promise for automated image analysis, a rigorous synthesis of its diagnostic accuracy across heterogeneo...

Grid-constrained peer-to-peer energy trading: enforcement-mechanism selection, personalized federated forecasting and auditable energy-quantity settlement

Decentralized energy markets can coordinate distributed generation, flexible demand and storage, but feeder feasibility, household forecasting and smart-contract settlement are usually assessed separately. This study develops a grid-constrained Decentralized Energy Marketplace (DEM) linking household commitments, bilat...

Defending Against Cyber Threats in the Smart Healthcare Ecosystem

This book offers a practical guide to securing smart Internet of Things (IoT)-based healthcare devices against cyber threats through hands-on tools, threat modeling, risk scoring, and artificial intelligence (AI)-enhanced defenses. Healthcare is undergoing rapid digital transformation, with smart IoT devices from weara...

Securing AI Chatbots: A Framework for Trust and Standardization

AI-based chatbots have taken over industries such as health care, finance, and customer services. However, the implementation of AI chatbots poses many issues regarding trust, privacy, and proper ethical use of this technology. This paper discusses a framework to standardize trust and security in AI-based chatbots. The...

PCOS-FedSev: Federated severity-aware PCOS diagnosis with site-invariant disentanglement and conformal guarantees

Abstract Polycystic ovary syndrome (PCOS) is a condition that affects between 8 and 13% of women during their reproductive years. However, PCOS continues to be vastly underdiagnosed despite its prevalence. Currently available AI-based PCOS diagnosis methods are limited by their centralized nature, making them difficult...

Poisoning Federated Knowledge Graph Embeddings Under Noisy Conditions

Navigating the privacy-accuracy tradeoff: federated survival analysis with binning and differential privacy

Federated Learning (FL) offers a decentralized approach to model training, allowing for data-driven insights while safeguarding patient privacy across institutions. In the Personal Health Train (PHT) paradigm, it is the local model gradients from each institution, aggregated over a sample size of its own patients that...