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 ...

Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a dataset that are different from the majority for tasks like ...

Dr. James McCaffrey of Microsoft Research tackles the process of examining a set of source data to find data items that are different in some way from the majority of the source items. Data anomaly ...

Violations of security policies within a computer or network are symbolic of the need for robust intrusion detection. From attackers accessing systems from the internet or authorized users conducting ...

Diagnostic tool for predictive maintenance in lyophilizers: an anomaly detection algorithm that flags abnormal patterns to cut downtime and costs. Get the essential updates shaping the future of ...

That challenge is examined in the study Towards Eco-Friendly Cybersecurity: Machine Learning-Based Anomaly Detection with ...

I am the VP of Engineering at Apriorit, a software development company that provides engineering services globally to tech companies. Social media is an indispensable tool for businesses to engage ...

Anomaly detection can be powerful in spotting cyber incidents, but experts say CISOs should balance traditional signature-based detection with more bespoke methods that can identify malicious activity ...