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A new approach to content-based file type detection

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3 Author(s)
Amirani, M.C. ; Dept. of Electr. Eng., Iran Univ. of Sci. & Technol. (IUST), Tehran, Iran ; Toorani, M. ; Beheshti, A.

File type identification and file type clustering may be difficult tasks that have an increasingly importance in the field of computer and network security. Classical methods of file type detection including considering file extensions and magic bytes can be easily spoofed. Content-based file type detection is a newer way that is taken into account recently. In this paper, a new content-based method for the purpose of file type detection and file type clustering is proposed that is based on the PCA and neural networks. The proposed method has a good accuracy and is fast enough.

Note: As originally published there is an error in the document's author byline. The name of the third author was listed as "Ali Asghar Beheshti Shirazi." The author wishes citations be credited to "Beheshti, A." The change is noted in Xplore's metadata but the PDF remains unchanged.  

Published in:

Computers and Communications, 2008. ISCC 2008. IEEE Symposium on

Date of Conference:

6-9 July 2008

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