Significant strides in addressing the issue of AI 'hallucinations' and improving the reliability of anomaly detection algorithms in Critical National Infrastructures (CNI) have been made by scientists ...

Imagine millions of lines of instructions. Then try and picture how one extremely tiny anomaly could be found in almost real-time and prevent a cyber security attack. Called a "program anomaly ...

Time-series data represents one of the most challenging data types for businesses and data scientists. The data sets are often very big, change continuously, and are time-sensitive by nature. One ...

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, ...

Security remains a dominant challenge in remote health monitoring. Medical data is deeply sensitive, and breaches can expose patients to identity theft, insurance exploitation or targeted cyberattacks ...

Leveraging the high performance, low-power design, and rich peripherals of AT32 MCUs—combined with the Edge Impulse platform— ...

When you think about it, financial technology, machine learning, and anomaly detection are proving indispensable in today’s time. Expert data scientists are transforming financial systems, adopting ...

Industrial processes and manufacturing systems depend on consistency and accuracy. Unusual data readings, or anomalies, can signal issues like equipment malfunction, faulty components or deteriorating ...