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A novel neural network approach for digital image data encryption/decryption

机译:一种用于数字图像数据加密/解密的新型神经网络方法

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摘要

With the increased popularity of multimedia applications, there is a great demand for secured data storage and transmission techniques. Information security has traditionally been ensured with data encryption and authentication techniques. Through the years, different generic data encryption standards have been developed. The secrecy of communication is maintained by secret key exchange. In effect the strength of the algorithm depends solely on the length of the key. The presented work aims at secure image transmission using randomness in encryption algorithm, thereby creating more confusion to obtain the original data. The security of the original cipher has been enhanced by addition of impurities to misguide the cryptanalyst. Since the encryption process is one way function, the artificial neural networks are best suited for this purpose as they possess features like high security, no distortion and its ability to perform for non linear input-output characteristics, In the presented work the need for key exchange is also eliminated, which is otherwise a perquisite for most of the algorithms used today. The proposed work finds its application in medical imaging systems, military image database communication and confidential video conferencing, and similar such application. The results are obtained through the use of MATLAB 7.0.1.
机译:随着多媒体应用的日益普及,对安全数据存储和传输技术的需求很大。传统上,通过数据加密和身份验证技术来确保信息安全。多年来,已经开发了不同的通用数据加密标准。通信的保密性通过密钥交换来保持。实际上,算法的强度仅取决于密钥的长度。提出的工作旨在使用加密算法中的随机性进行安全的图像传输,从而造成更多的混乱以获取原始数据。通过添加杂质以误导密码分析者,可以提高原始密码的安全性。由于加密过程是一种单向功能,因此人工神经网络具有高度的安全性,无失真及其对非线性输入输出特性的执行能力,因此最适合此目的。在目前的工作中,需要密钥交换也被消除了,否则这对于当今使用的大多数算法都是足够的。拟议的工作在医学成像系统,军事图像数据库通信和机密视频会议以及类似的此类应用中得到了应用。通过使用MATLAB 7.0.1获得结果。

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