federated learning

AI-Driven Intrusion Detection for Vehicular Networks: A Comprehensive Survey of Techniques, Datasets, Deployment Architectures, and Future Directions

Intelligent transportation systems (ITSs), Vehicle-to-Everything (V2X) communication and autonomous driving technologies have brought about significant changes in the modern vehicular network. At the same time, the cyber-attack surface has grown, leading to new and existing advanced security threats for Vehicular Ad ho...

FraudGraph-X: Privacy-Preserving Temporal Graph Learning for Scalable and Explainable Financial Fraud Detection

Review of bearing fault diagnosis based on neural networks

Bearings are critical components in rotating machinery, and their condition directly determines the operational efficiency and safety of industrial equipment. Traditional bearing fault diagnosis methods rely heavily on manual feature extraction, making it difficult to deal with complex industrial scenarios such as stro...

Reconfigurable trustless digital twins for continuous patient monitoring: A federated learning-blockchain architecture in healthcare 5.0

Poster: CMA-FL: Cognitive Multi-Agent Federated Learning for Resource-Aware Drone Communication Attack Detection

CMA-FL is proposed, a cognitive multi-agent assisted FL framework for resource-aware intrusion detection in drone communication networks that achieves 99.6% accuracy with 0.99 precision, recall, and F1-score and reduces response time by more than 80% relative to the evaluated FL, edge-cloud, and cloud-only alternatives...

An Analysis of Object Detection in Bad Weather Conditions using Deep Learning Models

Object detection, a task, in the field of computer vision faces obstacles when dealing with weather conditions such as fog, rain, snow, and low light situations. This paper provides an overview of advancements in the realm of object detection under challenging weather conditions. It delves into groundbreaking research...

Exploring the Landscape of Cloud Robotics: A Comprehensive Review

Cloud robotics is an innovative field that leverages cloud technologies-including cloud computing (CC), cloud storage, deep learning, big data, and the Internet of Things to augment the capabilities of robotics. This integration facilitates the execution of robotic functions through a converged infrastructure and share...

Future Trends in AI, Machine Learning, and Big Data: Implications for Technical Leadership

There's no denying that Artificial Intelligence (AI), Machine Learning (ML), and Big Data technologies are profoundly changing the face of software engineering and organizational leadership. As these technologies keep evolving, the design, deployment, and management of software systems are undergoing unprecedented chan...

AI Agentic Architectures for Autonomous Data Engineering Pipelines

This study delves into the notion of AI agentic architectures for autonomous data engineering pipelines and investigates the potential benefits of intelligent agents in enhancing automation, resilience, and decision-making processes in contemporary data ecosystems.

Policy Drift in Learning AI Agents: A Dynamical Systems Perspective on Security Degradation

Policy drift takes shape through a nonlinear differential equation - framed within the policy state space - with support from Lyapunov stability concepts alongside bifurcation methods alongside bifurcation methods, and the Intent Drift Rate appears: a concrete number per dialogue turn built as the time-based change in...

AI-driven cybersecurity in software engineering

AI-driven cybersecurity in the software engineering field is discussed, where machine learning, deep learning, natural language processing, and reinforcement learning can be applied throughout the software development lifecycle to provide increased security.

Designing Self-Healing AI Agentic Systems: A Framework for Autonomous Detection and Response

A new scientific object – the Autonomous Recovery Efficiency Score (ARES) – is introduced – a quantitative measure of autonomous resilience, as well as a supporting foundation for future autonomous self-healing AI agentic infrastructure.