Abstract: There is described herein a method for detecting anomalies in an infrastructure, the method comprising: providing a computationally-intelligent analysis model to model a behaviour of at least one detection instrument in said infrastructure; inputting control instrument data into said analysis model, said control instrument data being provided by control instruments in said infrastructure; outputting an estimated behaviour for said at least one detection instrument from said analysis model; comparing actual data from said at least one detection instrument to said estimated behaviour and generating a set of residuals representing a difference between said actual data and said estimated behaviour; and identifying anomalies when said residuals exceed a predetermined threshold.

Abstract: A method of data sensor validation is disclosed. The method comprises the steps of pre-processing data sensor from each sensor from a plurality of sensors for at least segmenting the data sensors into a plurality of groups, each group for grouping sensors for sensing highly relevant data one to another; providing the pre-processed data sensor to a correlation processor, the correlation processor for determining from pre-processed data sensor, pre-processed data that is other than correlated, the determination made in dependence upon redundant pre-processed data other than pre-processed data from two sensors for sensing an identical parameter; and, when pre-processed data that is other than correlated is detected, providing an indication to an operator that the sensor data is other than correlated.