[Click on image for larger view.] Figure 1: Autoencoder Anomaly Detection in Action This article assumes you have an intermediate or better familiarity with a C-family programming language, preferably ...

Anomaly detection is one of the more difficult and underserved operational areas in the asset-servicing sector of financial institutions. Broadly speaking, a true anomaly is one that deviates from the ...

Data from New Zealand’s National Climate Network are operationally verified both during data ingest and post data ingestion into the National Climate Database. The quality control process in the ...

Anju Kambadur, Bloomberg’s Head of AI Engineering, helped organize today’s 2nd KDD Workshop on Anomaly Detection in Finance, which is taking place during the 25th ACM SIGKDD Conference on Knowledge ...

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 ...

(1) An approach to intrusion detection that establishes a baseline model of behavior for users and components in a computer system or network. Deviations from the baseline cause alerts that direct the ...

Identifying anomalies in the operations of computer systems that control critical safety and security functions calls for extensive expertise, and the actions required need to be tested, analysed and ...

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 ...