With the continuous upgrading of network attacks, network abnormal traffic detection has become a key technology to ensure network security. However, existing detection methods still face challenges ...

Current intelligent grid anomaly detection faces challenges such as low minority-class recognition due to imbalanced data, high computational complexity in long-sequence processing, and model bias ...

The proposed industrial anomaly detection model is computationally efficient, memory-friendly, and also suitable for low-light conditions, common in manufacturing environments, making it well-suited ...

Dr. James McCaffrey from Microsoft Research presents a complete program that uses the Python language LightGBM system to create a custom autoencoder for data anomaly detection. You can easily adapt ...

Researchers have developed a new artificial intelligence-based system designed to improve cyberattack detection in ...

Anomaly detection is the process of identifying events or patterns that differ from expected behavior. Anomaly detection can range from simple outlier detection to complex machine learning algorithms ...