Abstract: Objective: The aim of my project was to implement the most recently published fully homomorphic encryption scheme. The idea behind this is to protect the data which needs to be shared with others in order for them to work on it without knowing the details of it. Introduction: Homomorphic encryption – encryption that supports operations on encrypted data – has a wide range of applications in cryptography. The concept was first introduced in 1978 by Rivest et al. shortly after the discovery of public key cryptography [1], and many popular cryptosystems, such as unpadded RSA or ElGamal, support either addition or multiplication of encrypted data. It was only in 2009 however, that Craig Gentry discovered the first plausible construction of a fully homomorphic encryption system supporting both operations [2].

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Abstract: Epigraphs are the important source for reshaping the history and the culture of our ancient civilizations. They have a remarkable importance to mankind. In India, the scripts of modern languages have evolved over a period of time and has finally transformed to the present form. Modern epigraphists find it difficult to interpret the scripts of olden days. The characters have changed over the centuries from one form to another. Therefore, for reading ancient scripts the period of that script has to be determined, so as to have knowledge of which character set of ancient days is to be employed for automatic reading. In this paper we demonstrate period identification of various ancient Kannada scripts using advanced recognition algorithms. Proposed algorithm involves various modules including image acquisition, noise removal, segmentation of character sets for feature extraction, classification and recognition of segmented characters. A system is proposed for prediction of the era and it i

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Abstract: Visibility Restoration of single hazy images based on, Colour Analysis and Depth Estimation on Bi-orthogonal Wavelet Transform with Enhanced refined transmission, we proposed an effectively local similarity based adaptive wavelet fusion method for reducing blocky artifacts, which is the major novelty of this work , performance of proposed dehazing method is evaluated on a series of hazy images and compared with several well-known single image dehazing methods. Estimate the dark channel prior based on average. Estimate the value of Air light based on standard deviation (which is a result of standard deviation of RGB haze image and HSV color space haze image), we suggested many rules based on experiments. We suggested to enhance the contrast by local contrast for (V) channel in the HSV color space. Results was very promised visually and by using some quality metrics.

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