Spatial-Temporal Anomaly Detection Using Security Visual Analytics via Entropy Graph and Eigen Matrix

Much of the big data which is produced is due to IoT devices and various sensor networks. This data often comes with spatial as well as temporal properties that can tell investigators many things about the environment in which they are located. For security practitioners, how to find abnormal activities or anomalies in the vast amount of spatial-temporal dynamic data is a daunting task. We present a system, STAnD, to assist investigators in determining patterns within these spatial-temporal data sets. The analysis conducted by using this program can support correlating events in both the spatial and temporal domains which will lead the investigators to determine probable causes for potential malicious events.