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Random Projection Method for Scalable Malware Classification

In this poster a new approach for scalable behavioral based malware classification is presented. It is based on the random projection method which is an efficient, effective yet simple dimensionality reduction method. Interestingly, however, the random projection method has not – to the authors’ best knowledge – ever been investigated for its possible usefulness for the malware classification problem. Here, we – for the first time – demonstrate its ability to reduce the dimensionality and to retain the properties of the data important for malware classification; it speeds up the distance calculations by an order of magnitude and yet it does not sacrifice much of the accuracy.