933 research outputs found

    Security System for Safe Transmission of Medical Images

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    This paper develops an optimised embedding of payload in medical images by using genetic optimisation. The goal is to preserve the region of interest from being distorted because of the watermark. By using this system there is no need to manually define the region of interest by experts as the system will apply the genetic optimisation to select the parts of image that can carry the watermark guaranteeing less distortion. The experimental results assure that genetic based optimisation is useful for performing steganography with less mean square error percentage

    Data Hiding in Gray-Scale Images by LSB Method using IWT with Lifting Scheme

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    This paper introduced a completely unique steganography technique to extend the capability and therefore the physical property of the image once embedding. Genetic rule utilized to get associate degree optimum mapping operate to minimize the error distinction between the quilt and therefore the stego image and use the block mapping technique to preserve the native image properties. Additionally we have a tendency to applied the OPAP to extend the activi ty capability of the rule comp are d to different systems. However, the process complexity of the new rule is high. The simulation results showed that capability and physical property of image had enl arg ed timing. Also, we will choose the most effective blo ck size to scale back the computation value and to extend the PSNR victimisation optimisation algorithms like GA

    A Study of Data Security on E-Governance using Steganographic Optimization Algorithms

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    Steganography has been used massively in numerous fields to maintain the privacy and integrity of messages transferred via the internet. The need to secure the information has augmented with the increase in e-governance usage. The wide adoption of e-governance services also opens the doors to cybercriminals for fraudulent activities in cyberspace. To deal with these cybercrimes we need optimized and advanced steganographic techniques. Various advanced optimization techniques can be applied to steganography to obtain better results for the security of information. Various optimization techniques like particle swarm optimization and genetic algorithms with cryptography can be used to protect information for e-governance services. In this study, a comprehensive review of steganographic algorithms using optimization techniques is presented. A new perspective on using this technique to protect the information for e-governance is also presented. Deep Learning might be the area that can be used to automate the steganography process in combination with other method

    A review and open issues of multifarious image steganography techniques in spatial domain

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    Nowadays, information hiding is becoming a helpful technique and fetch more attention due fast growth of using internet, it is applied for sending secret information by using different techniques. Steganography is one of major important technique in information hiding. Steganography is science of concealing the secure information within a carrier object to provide the secure communication though the internet, so that no one can recognize and detect it’s except the sender & receiver. In steganography, many various carrier formats can be used such as an image, video, protocol, audio. The digital image is most popular used as a carrier file due its frequency on internet. There are many techniques variable for image steganography, each has own strong and weak points. In this study, we conducted a review of image steganography in spatial domain to explore the term image steganography by reviewing, collecting, synthesizing and analyze the challenges of different studies which related to this area published from 2014 to 2017. The aims of this review is provides an overview of image steganography and comparison between approved studies are discussed according to the pixel selection, payload capacity and embedding algorithm to open important research issues in the future works and obtain a robust method

    Digital multimedia archiving based on optimization steganography system

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    © 2014 IEEE. As soon as digital artifacts have become a part and parcel of everyday life, the need for digital media archives with the capacity of preserving the given metadata has risen impressively. The process of converting the digital metadata to archives, however, is fraught with a number of difficulties, the key one concerning the methodology for embedding high payload capacity information into the digital multimedia and at the same time retains high quality of the image. The given paper will consider steganography as a possible solution to the aforementioned issue. Allowing for detecting the genetic algorithm for boosting the PSNR value with the information of high capacity will help solve the issue regarding the digital multimedia archiving. Many sizes of data are embeded inside the images and the PSNR (Peak signal-to-noise ratio) is also taken for each of the images verified

    LWT based encrypted payload steganography

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    Steganography is used in covert communication for transportation of secrete information. In this paper we propose LWT based Encrypted Payload Steganography (LEPS). The payload is segmented into two parts say block 1 and block 2. The LWT is applied on block 2 to generate four sub bands. Payload block 1 is retained in the spatial domain itself. The values of approximation band coefficients of block 2 and spatial domain intensity values of block 1 are compressed. The LWT is applied on cover image to generate wavelet sub bands and considered only diagonal sub bands (XD). The XD band is decomposed into three parts. The key values are embedded into first part of XD band. The compressed payload is embedded in second and third blocks of XD adaptively. The payload can be retrieved at the destination by adapting reverse process of embedding. It is observed that the values of PSNR and capacity are better in the case of proposed algorithm compared to existing algorithm
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