Authentication Of Critical Data Using Image Processing

being attacked, encrypt it with a secret key to obtain an encrypted bit stream . For that AES encryption is used. After AES encryption, will embed at the fourth bit position of . Some related information about the mosaic image generation process into the mosaic image for use in the secret image recovery process are also embed at the last fourth bit position of . Such information, described as a bit stream I like M, includes the following data items: 1) encryption key; and 2) total length of before encryption. After all this process Target image with mosaic image, residual value and all information that required to recover original image are transmitted to receiver

M2 – Explain the operation and use of encryption technique in ensuring security of transmitted information

Utilising cryptography to secure medical images and prevent both tampering and the re-identification requires a two step process involving the insertion of cryptographic algorithms and watermarking onto the image, this is able to completed without amending or hindering the pixel quality and retaining the integrity of the images (Kester et al., 2015). Additionally, the watermark can be encrypted using an advanced encryptions standard (AES) to assist in maintaining patient privacy from being re-identified (Abd-Eldayem,

Information security is a major concept in today’s industrial and computer era, so security must be higher to protect the confidential data. Information security plays major role in computer and network security with the use of different cryptography algorithms that includes the encryption and decryption of data with the uses of the algorithm and the key. By means of text or numerical key for the encryption can be dangerous because with the several hack attacks that a key can be broken. So I have proposed a new mechanism that will replace the text key with the image pixels and can gain high security which cannot be easy to break without prior knowledge.

Let CC denotes the cover carrier, Image IM, and CS the stego-image. Let S represent an optional key (a seed used to encrypt the message) and let SM be the message we want to communicate, image, i.e., image K.

Image domain also known as spatial domain techniques; embed messages in the intensity of the pixels directly. In transform domain; also known as frequency domain, images are first transformed and then the message is embedded in the image. Image domain techniques encompass bit-wise methods that apply bit insertion and noise manipulation and are sometimes characterized as “simple systems”. The image formats that are most suitable for image domain steganography are lossless and the techniques are typically dependent on the image format. Steganography in the transform domain involves the manipulation The main purpose of Steganography, which means ‘writing in hiding’ is to hide data in a cover media so that others will not be able to notice it. While cryptography is about protecting the content of messages, steganography is about concealing their very existence [1]. The applications of information hiding systems mainly range over a broad area from military area, intelligence agencies, internet banking, online elections, medical-imaging and so on. The cover medium is usually chosen keeping in mind the type and size of the secret message and many different type carrier file formats can be used. These variety of applications make steganography a hot

Abstract— Steganography is a technique of hiding the secret information. Steganography hides the existence of the secret data and make the communication undetectable. Secret data can be communicated in an appropriate multimedia carrier such as image, audio or video. Image steganography is extensively used technique. In this technique secret data is embedded within the image. Steganography techniques can be categorized into two groups - adaptive and non-adaptive. Each of these have its strengths and weaknesses. Adaptive steganography embeds the secret information in the image by adapting some of the local features of the image. Non-adaptive steganography embeds secret data equally in each and every pixel of the image. Several techniques have been proposed for hiding the

In the present world lot of multimedia data is exchanged on internet and the percent of image data in that is highest. So we need to securely transmit that and this can be achieved by Image encryption.

Abstract—Automatic recognition of people is a challenging problem which has received much attention during recent years due to its many applications in different fields. Face recognition is one of those challenging problems and up to date, there is no technique that provides a robust solution to all situations. This paper presents a technique for human face recognition. A self-organizing program is used to identify if the subject in the input image is “present” or “not present” in the image database. Face recognition with Eigen values is carried out by classifying Eigen values in both images. The main advantage of this technique is its high-speed processing capability and low computational requirements, in terms of both speed, accuracy and memory utilization. The goal is to implement the system for a particular face and distinguish it

Often there has been a need to protect information from 'prying eyes'. In the electronic age, information that could otherwise benefit or educate a group or individual can also be used against such groups or individuals. Industrial espionage among highly competitive businesses often requires that extensive security measures be put into place. And, those who wish to exercise their personal freedom, outside of the oppressive nature of governments, may also wish to encrypt certain information to avoid suffering the penalties of going against the wishes of those who attempt to control.

The core idea of this image encryption scheme (Tiegang Gao et al.,2007) is based on total shuffling matrix using the Logistic map, and the substitution of the shuffled image with a keystream

In the version of security analysis and experimental results our proposed encryption scheme is fast and on the other hand provides good security and adds very less overhead on the data, this today is the requirement of most of the multimedia applications.

The role of the user is limited to uploading files to the system,encrypting them with the AES encryption technique,signing the resulting encrypted files and creating the storagerequest. In addition, the user also generates the key to AES system by his ID and PASSWORD. It works as file identifier to the system. For each file, this key will be used to decrypt and re-build the file when it will be retrieved. Instead, thefile identifier is necessary to univocally identify a file overthe whole system. Finally, the user also signs each files with a special signature scheme. In order not to apply costly signatureoperations for the file, for all it adds owner name to a separate MM. The main architecture is illustrated in Fig. 5.1.

Abstract. The growth of internet coupled with the rise in networked infrastructure has resulted in exponential increase in the multimedia content being shared over the communication networks. The advancement in technology has resulted in increase in multimedia piracy. This is due to the fact that it is very easy to copy, duplicate and distributes multimedia content using current day technology. In such a scenario Digital Rights Management is one of the prominent issues to be dealt with and tremendous work is going on in this direction round the globe. Digital watermarking and fingerprinting have emerged as fundamental technologies to cater to DRM issues. These technologies have been found to be of prominent use in content authentication, copy protection, copyright control, broadcast monitoring and forensic applications. Various requirements of a digital watermarking system include Imperceptibility, Robustness, Security, Payload and Computational complexity. The main requirement of real time DRM systems is lesser computational complexity and high robustness. This chapter proposes and analyses a robust and computational efficient Image watermarking technique in spatial domain based on Inter Block Pixel Difference (IBPD). The cover image is divided into 8×8 non overlapping blocks and difference between intensities of two pixels of adjacent blocks at predefined positions is calculated. Depending upon the watermark bit to be embedded; both the pixels are modified to bring the

The algorithms are called Keygen, Encode, and Distance. Keygen is a probabilistic algorithm that is ran by a client to setup the scheme. Keygen generates a secret key along with a distance threshold and passes it to the Encode algorithm. With Encode, a deterministic algorithm, plaintext is encoded with the previous key by the client. During the last phrase, Distance, the server takes two encodings, one for plaintext and the other for distance to carry out the encryption. The authors went on to present two efficient implementations of DPE, one for dense media types, such as images, and the other for sparse media, such as text. Both implementations proved a secure realization of DPE. Without DPE MIE would be useless, as the users information would still be leaked.