Enterprise cybersecurity has shifted from human‑driven patching to autonomous AI warfare. Google Cloud’s Threat Defence initiative redefines contextual triage, remediation, and India’s regulatory edge ...

Apps that record visits are becoming popular, but they come with privacy and accuracy concerns. By Simar Bajaj At your next appointment, your doctor may have a new kind of assistant listening in: ...

Industrial Control Systems (ICS) are becoming more important than ever because most of the essential services we use in our daily life depends on them, such as electricity supply, clean water ...

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 ...

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 ...

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...

ABSTRACT: Video-based anomaly detection in urban surveillance faces a fundamental challenge: scale-projective ambiguity. This occurs when objects of different physical sizes appear identical in camera ...

System logs are run-time significant events of computer systems recorded by software. By analyzing the system logs, a lot of important information and issues can be detected promptly. Log anomaly ...

In-line sensors, which are crucial for real-time (bio-) process monitoring, can suffer from anomalies. These signal spikes and shifts compromise process control. Due to the dynamic and non-stationary ...

Abstract: Anomaly detection (AD) is typically regarded as an unsupervised learning task, where the training data either do not contain any anomalous samples or contain only a few unlabeled anomalous ...