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AN EFFICIENT NEURAL NETWORK BASED ALGORITHM FOR DETECTING STEGANOGRAPHY CONTENT IN CORPORATE MAILS: A WEB BASED STEGANALYSIS

Steganography refers to information or file that has been concealed inside a digital media. Steganalysis is used to detect and/or estimate potentially hidden information from observed data with a little or no knowledge about the steganography algorithm and its parameters. Current trend in steganalysis seems to suggest two extreme approaches (a) little or no statistical assumption about the image under investigation. Statistics are learnt using a large database of training image and (b) a parametric model is assumed for the image and its statistics are computed for steganalysis detection. This research developed a new hybrid approach which comprises of neural network and S-DES encryption scheme which is used to detect the stego content in corporate mails. In this research work we implemented the combination of Compression, Encryption, Steganography to enhance the security of the data sent and Steganalysis methods which will detect the stego content in corporate emails. This method will be used to enhance the security measures of corporate mails.