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This paper proposes a method, called Oscar, for determining the probable file type of binary data fragments. The Oscar method is based on building models, called centroids, of the mean and standard deviation of the byte frequency distribution of different file types. A weighted quadratic distance metric is then used to measure the distance between the centroid and sample data fragments. If the distance falls below a threshold, the sample is categorized as probably belonging to the modelled file type. Oscar is tested using JPEG pictures and is shown to give a high categorization accuracy, i.e. high detection rate and low false positives rate. By using a practical example we demonstrate how to use the Oscar method to prove the existence of known pictures based on fragments of them found in RAM and the swap partition of a computer.

Oscar — File Type Identification of Binary Data in Disk Clusters and RAM Pages