We present a fully homomorphic encryption scheme which has both relatively small key and ciphertext size. Our construction follows that of Gentry by producing a fully homomorphic scheme from a “somewhat” homomorphic scheme. For the somewhat homomorphic scheme the public and private keys consist of two large integers (one of which is shared by both the public and private key) and the ciphertext ...

We study homomorphic authenticated encryption, where privacy and authenticity of data are protected simultaneously. We define homomorphic versions of various security notions for privacy and authenticity, and investigate relations between them. In particular, we show that it is possible to give a natural definition of IND-CCA for homomorphic authenticated encryption, unlike the case of homomorp...

A new method, homomorphic e-auction based on multiplicative homomorphic encryption algorithm like ElGamal encryption is proposed in this paper. Its advantage is obvious and useful in practice: efficient distributed private key generation and thus efficient trust sharing. A long existing problem in homomorphic e-auction, inefficiency of bid validity check, is solved in the new multiplicative hom...

This article discusses methods of abnormal audio detection. Extract information from acquisition hardware, convert analog signals into digital signals, perform pre-focused processing on and compare analyze noise reduction algorithms, such as wave reduction, homomorphic filtering, Wiener filtering. After is performed the data, endpoint detection continuous frequency actual segment separated sign...

This report presents a theory of quantized systems in support of predictive filtering based on a process called "quantization" to reduce state update transmission. A quantized system is a system with input and output quantizers. Quantization, which generates state updates only at quantum level crossings, abstracts a sender model into a DEVS (Discrete Event System Specification) representation. ...

In this chapter, the authors provide an overview of state-of-the-art image enhancement and restoration techniques for underwater images. Underwater imaging is one of the challenging tasks in the field of image processing and computer vision. Usually, underwater images suffer from non-uniform lighting, low contrast, diminished color, and blurring due to attenuation and scattering of light in the...

Collaborative Filtering (CF) is a method to perform Automated Recommendations based upon the assumption that users who had similar interests in past, will have similar interests in future too. Popularity of e-commerce portals such as Amazon and Ebay and Web 2.0 applications such as YouTube and Flickr is resulting in private user data being stored in central servers. This has given rise to a num...

An approach to multi-channel blind deconvolution is developed, which uses an adaptive filter that performs blind source separation in the Fourier space. The approach keeps (during the learning process) the same permutation and provides appropriate scaling of components for all frequency bins in the frequency space. Experiments verify a proper blind deconvolution of convolution mixtures of sources.

A key aspect for virtual-reality based ultrasound training is the plausible simulation of the characteristic noise pattern known as ultrasonic speckle. The formation of ultrasonic speckle can be approximated efficiently by convolving the ultrasound point-spread function (PSF) with a distribution of point scatterers. Recent work extracts the latter directly from ultrasound images for use in forw...

A very important artifact corrupting Magnetic Resonance (MR) Images is the RF inhomogeneity, also called Bias artifact. The visual effect produced by this kind of artifact is an illumination variation which afflicts these kind of medical images. In literature a lot of works oriented to the suppression of this artifact can be found; among them, those ones based on homomorphic filtering offer an ...