Network anomaly detection is an important and dynamic research area. Many Network Intrusion Detection methods and Systems (NIDS) have been proposed in the literature. In this paper, the authors ...
Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, ...
In this paper, a few methods for anomaly detection in computer networks with the use of time series methods are proposed. The special interest was put on Brown’s exponential smoothing, seasonal ...
Video-based anomaly detection in urban surveillance faces a fundamental challenge: scale-projective ambiguity. This occurs ...
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 ...
The US Army Analytics Group (AAG) provides analytical services for various organizational operations and functions, including cybersecurity. AAG signed a Cooperative Research and Development Agreement ...
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 ...
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 ...
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