Detecting Stego-Contents in Corporate E-Mails Using Back Propogation Neural Network Algorithm

Anitha Shyam


Information Security and integrity are becoming more important as we use email for personal communication and business. Steganography is used to hide the occurrence of communication. Today, email management is not only a filing and storage challenge. Because law firms and attorneys must be equipped to take control of litigation, email authenticity must be unquestionable with strong chains of custody, constant availability, and tamper-proof security. Email is insecure. This proposed will develop a steganalysis framework that will check the Email content of corporate mails by improving the S-DES algorithm with the help of neural network approach. A new filtering algorithm is also developed which will used to extract only the JPG images from the corporate emails. We anticipate that this paper can also give a clear picture of the current trends in steganography so that we can develop and improvise appropriate steganalysis algorithms.

In this paper we propose a new method based on neural network to get statistics features of images to identify the underlying hidden data. We first extract features of image embedded information, then input them into neural network to get output. And experiment results indicate this method is valid in steganalysis. This method will be used for Internet/network security, watermarking and so on.

Full Text:




Copyright (c) 2016 International Journal Series in Engineering Science (IJSES)

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.