Researchers at the University of Florida are developing artificial intelligence models to pinpoint early signs of sinkholes ...

Cyber threats are increasing in speed and complexity, driving the need for advanced detection techniques. Machine learning is ...

Discover how artificial intelligence is enhancing fraud detection across online platforms, using real-time analytics and ...

In today’s digital age, cyber threats are evolving faster than ever, forcing organizations to rethink traditional security measures. AI-powered cybersecurity ...

The Kill Chain models how an attack succeeds. The Attack Helix models how the offensive baseline improves. Tipping Points One person. Two AI subscriptions. Ten government agencies. 150 gigabytes of ...

The use of generative AI enables a novel computational approach to localize individual trees in all cities, despite their ...

An international research team developed a multi-stage intrusion detection system that uses supervised and unsupervised AI techniques to detect and mitigate cyber threats in smart renewable energy ...

Abstract: The explosive growth of the Internet of Things (IoT) has introduced vast amounts of data and unprecedented security challenges, making effective anomaly detection in IoT environments a ...

Abstract: Open-set Supervised Anomaly Detection (OSAD) strategy seeks to detect novel anomalies that are unseen during training. However, existing OSAD works fail to learn a comprehensive margin that ...

Real-time detection of anomalies in data streams is a foundation of modern applied analysis in complex systems. It enables experts to design rapid, efficient, reliable, and high-performance decision ...

The operation of fuel cell electric vehicle-to-grid (FCEV2G) stations presents a significant challenge due to the need to manage onsite hydrogen production, storage, and vehicle dispatch in volatile ...