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Corporations are dealing with the traditions of managing security in silos, leading to an increased number of attacks on things like critical infrastructure. Corporate (Physical) Security deals with facilities and building access, whereas IT Security is dealing with cybersecurity as well as system and network access. It’s as if they are living on different planets!

In this paper, we present Discriminant Correlation Analysis (DCA), a feature level fusion technique that incorporates the class associations in correlation analysis of the feature sets. DCA performs an effective feature fusion by maximizing the pair-wise correlations across the two feature sets, and at the same time, eliminating the between-class correlations and restricting the correlations to be within classes.