federated learning

Dataset and Experimental Results: Robust Aggregation Ranks the Free-Rider First

Prototype-based federated learning exchanges class-embedding matrices without exposing the computation that produced them. We evaluate three verification mechanisms against free-riding at this interface: robust aggregation used for contribution ranking, commitments to model behavior, and passport-derived identities. On...

Deep Reinforcement Learning for Security-Aware Task Offloading in IoT Edge Computing: A Systematic Survey of Frameworks, Challenges, and Future Directions

Background: IoT devices deployed in hospitals, factories, vehicles, and homes are largely unable to defend themselves. Limited compute and power budgets make running a local intrusion detector impractical, even as the traffic these devices generate grows increasingly attractive to attackers. DRL offers a practical alte...

Gozie01/ClinicalTrial.sol: Trust CT

Initial archived release of the TRUST-CT code and supporting materials for the federated learning, policy evaluation, security, and audit analyses.

A Privacy-Preserving Federated Data Exchange Architecture for Trusted Cross-Border Digital Services in the East African Community

The results show the potential of PP-FDEA for providing secure, privacy preserving, scalable and trusted EAC cross-border digital services.

World Scientific Committee for Planet Earth (WSCPE)

World Scientific Committee for Planet Earth (WSCPE) WSCPE proposes a new, standalone, voluntary and federated scientific and ethical coordination body for any technology with significant transboundary, systemic, planetary or intergenerational effects. It seeks verifiable and equitably distributed human progress under r...

A comprehensive survey of Edge-Fog-Cloud-IoT architectures: Intelligence, Security, and Sustainability

The rapid expansion of IoT devices has resulted in a paradigm shift from centralized cloud computing models to highly distributed computing continua that incorporate IoT devices, edge gateways, fog nodes, regional cloudlets, and hyperscale cloud data centers. In this survey, we provide an overview of Edge-Fog-Cloud-IoT...

Blockchain-based secure provenance and auditability mechanism for medical IoT devices in healthcare ecosystems

The increasing approval of Internet of Medical Things (IoMT) in healthcare produces large volumes of sensitive patient data, raising critical challenges in security, privacy, and integrity due to weaknesses in centralized systems. Such systems are prone to tampering, unauthorized access, and a lack of transparency, gen...

Integrated Anomaly Detection and Mitigation in SDN Environments: A Hybrid Approach

Modern network infrastructures are under attack from increasingly sophisticated attacks that static, rule-based defenses cannot adequately mitigate. We introduce a multilayer anomaly detection and mitigation framework for Software-Defined Networking (SDN) environments consisting of four integrated subsystems: (i) a Mic...

Federated Learning with Explainable Artificial Intelligence for Privacy-Preserving Skin Cancer Detection: A Multi-Institutional Study

Quantum-Assisted Federated Learning Based Privacy Preserving Medical Image Classification

Developing a Federated, Lightweight, Interpretable, and Specialized AI-Based Intrusion Detection System for Medical Internet of Things (IoMT) Environments

The rapid expansion of the Internet of Medical Things (IoMT) has enhanced healthcare services, but it has also exposed these systems to a growing range of cyberattacks. Addressing this challenge requires effective intrusion detection solutions. Machine learning-based intrusion detection systems (IDSs) offer a promising...

SemioKAT-FL: explainable, background-invariant, and privacy-preserving video seizure detection with a Kolmogorov–Arnold Transformer and federated learning

Abstract Automatic detection of epileptic seizures from video promises non-invasive, continuous patient monitoring, yet web-sourced seizure corpora are dominated by background confounds : recording-specific cues (studio, home, clinic) that are spuriously correlated with the seizure label. Models that appear highly accu...