Enhanced chimp optimization algorithm using crossover and mutation techniques with machine learning for IoT intrusion detection system
Published in: Cluster Computing
Jul 31, 2025
One of the most prevalent challenges nowadays is detecting intrusions into the Internet of Things (IoT) systems, which pose a variety of wide-ranging cyber threats. These devices encompass smart cities, industries, and homes, all integral to modern living. Their widespread adoption increases the urgency of addressing security vulnerabilities. Ensuring secure user interactions is of particular importance. This study proposes an intrusion detection approach that combines K-Nearest Niebuhr (KNN) a...
LSOARP: A Link Stability and Obstacle-Aware Routing Protocol for UAV Networks
Published in: Journal of Soft Computing and Data Mining
Jun 30, 2025
As using Unmanned Aerial Vehicles (UAVs) continues to grow across military, environmental, and public safety sectors, we are seeing a fast development of Flying Ad Hoc Networks (FANETs). Despite this progress, creating reliable routing protocols for UAVs remains complex because of their high mobility, constantly changing network topology, frequent link drops, and physical obstacles in the environment. Current protocols often overlook the importance of link stability and obstacle-aware navigatio...
Generalizing location-centric variations to enhance contactless human activity recognition
Published in: Frontiers in Computational Neuroscience
Jun 19, 2025
Contactless Human Activity Recognition (HAR) has played a critical role in smart healthcare and elderly care homes to monitor patient behavior and detect falls or abnormal activities in real time. The effectiveness of non-invasive HAR is often hindered by location-centric variations in Channel State Information (CSI). These variations limit the ability of HAR models to generalize across new unseen cross-domain environments; for instance, a model trained in one location might not perform well in...