The week's pick
Reseach Article
Steganography Detection using Functional Link Artificial Neural Networks
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 47 - Number 5 |
| Year of Publication: 2012 |
| Authors: Ch. Demudu Naidu, S. Pallam Setty, M. James Stephen, S.k.prashanth, Ch. Suresh |
10.5120/7182-9882
|
Ch. Demudu Naidu, S. Pallam Setty, M. James Stephen, S.k.prashanth, Ch. Suresh . Steganography Detection using Functional Link Artificial Neural Networks. International Journal of Computer Applications. 47, 5 ( June 2012), 6-10. DOI=10.5120/7182-9882
Abstract
Security in message transfer over the netwoek has been a consistent challenge in the field of I. T. Cryptography is one of very much spoken solution. Security of messages that are being transferred is very important and experts have lot of work to think of new techniques and approaches in cryptography. At the same time cryptanalysts also have very important job to detect and reveal and then decode the coded messages. Steganography is another additional method for better secure up messages which goes hand by hand with cryptography, and reveal of such a message is not easy. In this paper, we presented a new approach known as Steganography detection using Functional Link Artificial Neural Networks that deals with neural network models that are able to detect Steganography content coded by a program Outguess. Neural network methods are flexible in learning various typical problems. In this paper 'Functional Link Artificial Neural Network' is used which is one of the methods for training a neural network. Results in this project show that used model had almost 100% success in revealing Steganography by means of Outguess.
References
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