Designing an Efficient Image Encryption-Then- Compression System with Haar and Daubechies Wavelet

Nowadays there is development in the multimedia and network technologies. That’s why the privacy and security becomes the major issues since the multimedia is transmitted openly over the network .so that Along with privacy and security, the space of s storage is also an important point that can’t be missed. So that, provide the privacy and security to the multimedia, encryption work as the similarly of root to reduce the storage space compression can be used. Reduction size also reducing the time taken for transmission. In many practical experiments, image encryption to be conducted prior to image compression. This has to be the problem, how to design a pair of image encryption and compression algorithms such that compressing the encrypted images can still be efficiently performed. In this research work, we design the algorithm and implement an efficient image encryption compression system. The proposed image encryption method is operated with random permutation method which is shown to be providing reasonably high level of security. We also have implement the new kind of image compression algorithm using Haar and Daubechies Wavelet Transform can be used to efficiently compress the encrypted image. Moreover, the compression approach applied to encrypted image is proved more efficient in terms of Compression Ratio (CR), Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR). For the implementation of this proposed work we use the Image Processing Toolbox under MATLAB software. Keywords—ETC, Haar Wavelet and Daubechies Wavelet. I.INTRODUCTION The development of multimedia and network technologies, the security of multimedia application becomes more and more important, when the multimedia data are transmitted over open networks more and more frequently. Moreover, reliable security is necessary to content protection of digital images and videos. Encryption Techniques for multimedia data needs has to be specifically designed to protect multimedia content and fulfill the security requirements for a particular multimedia application. For example, the realtime encryption of an entire video stream using classical ciphers requires heavy computation due to the large amounts of data involved, but many multimedia applications require security on a much lower level, that can achieved using selective encryption that leaves some perceptual information after encryption. Government private business, and military, a mass great deal of confidential images about their patient (in Hospitals), geographical areas (in research), enemy positions (in defense), financial-status. Most of these information are now collected and stored on electronic computers and transmitted across network to other computer, if this confidential images about enemy positions ,patient ,and geographical areas fall into the wrong hands, After than such a breach of security could lead to lots of war , wrong treatment etc. Protecting confidential images is an ethical and legal requirement. We store information in computer system in the form of files. Files are considered or defined as a basic entity for keeping the information. Then the problem of securing image data or information on computer system can be defined as the problem of securing file data. It is worldwide accepted fact that securing file data is very important, in today’s computing environment. Good encryption makes a source look completely random, previous or traditional algorithms are unable to compress encrypted data. For this reason, traditional systems make sure to compress before they encrypt. We are using the concept of public key encryption, for the encryption and decryption of image. In this public key’s of sender and receiver is known to both but private key’s are kept secret. Neither the security nor the compression efficiency will be sacrificed by performing compression in the encrypted domain. Consider an application scenario in which a content owner Alice wants to securely and efficiently transmit an image I to a recipient Bob, via an un-trusted channel provider Charlie. Conventionally, this could be done as follows. Alice first compresses I into B, and then encrypts B into Ie using an encryption function EK (・), where K denotes the secret key. The encrypted data Ie is then passed to Charlie, who simply forwards it to Bob. Upon receiving Ie, Bob sequentially performs decryption and decompression to get a reconstructed image I. Even though the above Compression-then-Encryption (CTE) paradigm meets the requirements in many secure transmission scenarios, order to applying the compression and encryption needs to be reversed in some other situations. As the content owner, always Alice is interested in protecting the privacy of the image data through encryption. Nevertheless, Alice has to be no incentive to compress data, and will not use her limited computational resources to run a compression algorithm before encrypting the data, especially true when Alice uses a resourcedeprived mobile device. In the contrast, channel provider Charlie has an overriding interest in compressing all the network traffic so as to maximize the network utilization. Therefore much desired if the compression task can be Harmanpreet Kaur Aujla et al, / (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 5 (6) , 2014, 7784-7788