Abstract. In modern world the use of digital devices for leisure or professional reasons (computers, tablets and smartphones etc.) is growing quickly. Nevertheless, criminals try to fool authorities and hide evidence in a computer or any other digital device, by changing the file type. File type detection is a very demanding task for a digital forensic examiner. In this paper a new methodology is proposed -in a digital forensics perspective-to identify altered file types with high accuracy by employing computational intelligence techniques. The proposed methodology is applied in the four most common types of files (jpg, png and gif). A three stage process involving feature extraction (Byte Frequency Distribution), feature selection (genetic algorithm) and classification (neural network) is proposed. Experimental results were conducted having files altered in a digital forensics perspective and the results are presented. The proposed model shows very high and exceptional accuracy in file type identification.

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