Radial Basis Function Neural Network for Image Steganalysis in Computer Forensics

P. Sujatha; S. Purushothaman; R. Rajeswari

Radial Basis Function Neural Network for Image Steganalysis in Computer Forensics

P. Sujatha, S. Purushothaman, R. Rajeswari

Abstract

The covert communication based on steganography is a challenging technology for governments. Using this most powerful technique terrorists and spies communicate with each other to exchange their plan which is not detected by law enforcement. In order to avoid the misusage of steganographic technique, the government needs to find out some powerful techniques to detect the existence of the hidden data in the digital media. This leads to the concept of steganalysis that is used in many fields such as digital forensics, medical imaging, and journalism. Apart from all modern sciences and technologies, Artificial Neural Network (ANN) plays a vital role in capturing and representing both linear and non-linear relationships. ANN is an intelligent system which enables machines to solve problems like human by extracting and storing the knowledge. Hence to incorporate intelligent method for steganalysis, this paper implements Artificial Neural Network to overcome the drawbacks of the conventional methods. The most powerful Radial basis function algorithm is proposed in this paper since it is more suitable for non-linear data. This paper concentrates on detecting the hidden information for digital forensics application.

Keywords

Artificial Neural Network, Covert Communication, Radial Basis Function (RBF), Steganography, Steganalysis

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