Imon Mukherjee

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Steganography plays an important role to hide data in apparently innocuous media (e.g., image, audio, video, text, etc.). Since most of the steganographic algorithms do not consider the image content while locating the message bearing pixels, in most occasions, they are bound to defeat against visual, structural and statistical attacks. We distribute the(More)
With the advancement of technology, the world has not only become a better place to live in but have also lost the privacy and security of shared data. Information in any form is never safe from the hands of unauthorized accessing individuals. Here, in our paper we propose an approach by which we can preserve data using visual cryptography. In this paper,(More)
Image sterilization is the process of removing steganographic information embedded in digital images. The only work known in this area is targeted to LSB-based steganography algorithm. In this paper, we extend the idea to sterilize two least significant bits of pixel intensities. The technique does not need to know how the information has been embedded(More)
Sterilization is a very popular word used in biomedical testing (like removal of all microorganisms on surface of an article or in fluid using appropriate chemical products). Motivated by this biological analogy, we, for the first time, introduce the concept of sterilization of an image, i.e., removing any steganographic information embedded in the image.(More)
Presently, in digital scenario, the most prime requirement is to secure data while transmitting through communication channel. Commonly, cryptography and steganography are used to achieve this purpose. In this work, we propose a novel spatial domain image steganography by converting the pixel intensity value into Triangular base. Our algorithm is capable of(More)
Science and technology devices pose new and vibrant solutions to the day to day problems faced by the Information Technology user society, data security issues are on the rise as well. Now-a-days security concerns are directly proportional with the steep hike in amount of data handled. The greatest threat comes from individuals who try to access information(More)
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