首页|Patent Issued for Anomaly detection in a split timeseries dataset (USPTO 1203253 8)
Patent Issued for Anomaly detection in a split timeseries dataset (USPTO 1203253 8)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
News editors obtained the following quote from the background information suppli ed by the inventors:“Timeseries data processing is used in various industries f or identifying patterns and anomalies. Forexample, in the cybersecurity industr y timeseries data may be used to identify anomalies that correspondto security threats or security breaches, which may be vital to many enterprises. In another example,timeseries data is used to determine anomalies in weather patterns. In yet another example, timeseriesprocessing is used by financial institutions to detect fraudulent activity or other activity that is out of theordinary (e.g., anomalous) and apply targeted defenses. Some anomaly detection scenarios suffer frominaccurate results, for example, cases where many/too many false positive results are detected (e.g., ananomaly has been detected, but no anomaly exists at the detection time). More recently, enterprises startedusing machine learnin g to build analysis models and to process timeseries data in order to more effic ientlyand accurately identify anomalies.”
BusinessCapital One Services LLCCybe rsecurityCyborgsEmerging TechnologiesMachine Learning
NETL
NSTL
