Stego- Cryptography Using Chaotic Neural Network
Narendra Kumar Kamila, Haripriya Rout, Nilamadhab Dash · American Journal of Signal Processing · 2014
Information protection is now a crucial problem and good solution to this problem is cryptography and steganography. The content of message is kept secret in cryptography, where as in Steganography; a message is embedded in a cover image. In our proposed work a system is developed in which LSB Steganography and Cryptography using chaotic neural network is combined together to provide high security to the message during communication in an unsecure channel. In LSB Steganography taking advantage of the way the human eye perceives images, the technique involves of replacing the N least significant bits of each pixel of a container image with the data of a hidden message. Cryptography based on chaotic neural network is used because of its noise like behaviour which is quite significant for cryptanalyst to know about the hidden information as it is hard to predict. Thus the information is being kept secret. In this work we have considered the advantages of both the concepts and developed a model in which initially a message is embedded in a gray scale image using LSB steganography and then the stegoimage is encrypted using chaotic neural network to provide high security to the message. The whole process is implemented using MATLAB. The simulation results show the robustness of the technique.