A new approach to content-based file type detection

Author

Amirani, M.C. ; Toorani, Mohsen ; Beheshti, A.

Author_Institution

Dept. of Electr. Eng., Iran Univ. of Sci. & Technol. (IUST), Tehran, Iran

fYear

2008

fDate

6-9 July 2008

Firstpage

1103

Lastpage

1108

Abstract

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.

Keywords

feature extraction; file organisation; neural nets; pattern clustering; principal component analysis; security of data; PCA; computer security; content-based file type detection; feature extraction; file extension; file type clustering; file type identification; magic bytes; network security; neural network; Accuracy; Artificial neural networks; Computers; Feature extraction; Neurons; Principal component analysis; Probability density function;

fLanguage

English

Publisher

ieee

Conference_Titel

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

Conference_Location

Marrakech

ISSN

1530-1346

Print_ISBN

978-1-4244-2702-4

Type

conf

DOI

10.1109/ISCC.2008.4625611

Filename

4625611