비만아 부모의 돌봄 경험: q 방법론

After two decades of research and development, elliptic curve cryptography now has widespread exposure and acceptance. Industry, banking, and government standards are in place to facilitate extensive deployment of this efficient public-key mechanism. Anchored by a comprehensive treatment of the practical aspects of elliptic curve cryptography (ECC), this guide explains the basic mathematics, describes state-of-the-art implementation methods, and presents standardized protocols for public-key encryption, digital signatures, and key establishment. In addition, the book addresses some issues that arise in software and hardware implementation, as well as side-channel attacks and countermeasures. Readers receive the theoretical fundamentals as an underpinning for a wealth of practical and accessible knowledge about efficient application. Features & Benefits: * Breadth of coverage and unified, integrated approach to elliptic curve cryptosystems * Describes important industry and government protocols, such as the FIPS 186-2 standard from the U.S. National Institute for Standards and Technology * Provides full exposition on techniques for efficiently implementing finite-field and elliptic curve arithmetic* Distills complex mathematics and algorithms for easy understanding* Includes useful literature references, a list of algorithms, and appendices on sample parameters, ECC standards, and software toolsThis comprehensive, highly focused reference is a useful and indispensable resource for practitioners, professionals, or researchers in computer science, computer engineering, network design, and network data security.

https://cdn.preterhuman.net/texts/cryptography/Hankerson,%20Menezes,%20Vanstone.%20Guide%20to%20elliptic%20curve%20cryptography%20(Springer,%202004)(ISBN%20038795273X)(332s)_CsCr_.pdf

Guide to Elliptic Curve Cryptography

National Institute of Standards and Technology における超伝導研究及び生活

Most of the signal processing that we will study in this course involves local operations on a signal, namely transforming the signal by applying linear combinations of values in the neighborhood of each sample point. You are familiar with such operations from Calculus, namely, taking derivatives and you are also familiar with this from optics namely blurring a signal. We will be looking at sampled signals only. Let's start with a few basic examples. Local difference Suppose we have a 1D image and we take the local difference of intensities, DI(x) = 1 2 (I(x + 1) − I(x − 1)) which give a discrete approximation to a partial derivative. (We compute this for each x in the image.) What is the effect of such a transformation? One key idea is that such a derivative would be useful for marking positions where the intensity changes. Such a change is called an edge. It is important to detect edges in images because they often mark locations at which object properties change. These can include changes in illumination along a surface due to a shadow boundary, or a material (pigment) change, or a change in depth as when one object ends and another begins. The computational problem of finding intensity edges in images is called edge detection. We could look for positions at which DI(x) has a large negative or positive value. Large positive values indicate an edge that goes from low to high intensity, and large negative values indicate an edge that goes from high to low intensity. Example Suppose the image consists of a single (slightly sloped) edge:

http://ieeexplore.ieee.org/iel5/5/31307/01456462.pdf

Linear systems

Ad hoc wireless networks enable new and exciting applications, but also pose significant technical challenges. In this article we give a brief overview of ad hoc wireless networks and their applications with a particular emphasis on energy constraints. We then discuss advances in the link, multiple access, network, and application protocols for these networks. We show that cross-layer design of these protocols is imperative to meet emerging application requirements, particularly when energy is a limited resource.

Design challenges for energy-constrained ad hoc wireless networks

In this paper, we investigate interleaved cyclic redundancy check (CRC) code. The interleaved CRC can be obtained by merging independent small message blocks into one large block (merged interleaving) or by dividing the original message block into independent small sub blocks (divided interleaving) and then by alternatively dividing the resulting message block(s) using same generator polynomial. The interleaved CRC increases both the detection span and the detectable error patterns. New applications of the interleaved CRC as the error detection scheme or stopping criteria in interleaved error correction coding and iterative decoding schemes are proposed. Since each individual codeword of interleaved CRC code is mutually independent, it is possible to generate CRC in interleaved manner and to check CRC in parallel manner.

Interleaved cyclic redundancy check (CRC) code

A new algorithm for resource-constrained scheduling for DSP applications is presented. New graph dependent constraints are defined. This directly results in the smallest iteration period for any data-flow graph. Previous synthesis systems have focused on simple DSP algorithms which contain no recursive loops or have single delays in the recursive loops. The MARS system is not restricted to such algorithms. This approach exploits inter-iteration precedence constraints, and incorporates implicit retiming and pipelining in generating optimal and near optimal schedules. >

Loop list scheduler for DSP algorithms under resource constraints

This paper considers implementation of artificial neural networks (ANNs) using molecular computing and DNA based on fractional coding. Prior work had addressed molecular two-layer ANNs with binary inputs and arbitrary weights. In prior work using fractional coding, a simple molecular perceptron that computes sigmoid of scaled weighted sum of the inputs was presented where the inputs and the weights lie between [-1, 1]. Even for computing the perceptron, the prior approach suffers from two major limitations. First, it cannot compute the sigmoid of the weighted sum, but only the sigmoid of the scaled weighted sum. Second, many machine learning applications require the coefficients to be arbitrarily positive and negative numbers that are not bounded between [-1, 1]; such numbers cannot be handled by the prior perceptron using fractional coding. This paper makes four contributions. First molecular perceptrons that can handle arbitrary weights and can compute sigmoid of the weighted sums are presented. Thus, these molecular perceptrons are ideal for regression applications and multi-layer ANNs. A new molecular divider is introduced and is used to compute sigmoid(ax) where a > 1. Second, based on fractional coding, a molecular artificial neural network (ANN) with one hidden layer is presented. Third, a trained ANN classifier with one hidden layer from seizure prediction application from electroencephalogram is mapped to molecular reactions and DNA and their performances are presented. Fourth, molecular activation functions for rectified linear unit (ReLU) and softmax are also presented.

Molecular and DNA Artificial Neural Networks via Fractional Coding

Stochastic computing using simple logic circuits requires significantly less area and consumes less power compared to traditional computing systems. These circuits are also inherently fault-tolerant. The main drawbacks of these systems include long latency and inexactness in computing. The deviation from exact values increases as the correlation among inputs increases. In many applications, outputs from different sensors may be correlated. Thus, testing correctness of stochastic computing circuits requires generation of correlated stochastic bit streams. While uncorrelated bit streams can be generated using linear feedback shift registers (LFSRs), generation of correlated stochastic bit streams has not yet been fully investigated. This paper presents a general approach to synthesize correlated stochastic bit streams for specified probabilities and specified correlation coefficients. Generation of N correlated stochastic bit streams requires N probabilities and 2N — N — 1 correlation coefficients. Using N LFSRs, N uncorrelated stochastic bit streams are first generated. The N correlated bit streams are then generated one at a time using conditional marginal probabilities. The method is illustrated for generating two and three correlated bit streams. The area and power overheads for two correlated bit streams are 9.09% and 2.12%, respectively, and for three correlated bit streams are 21.03% and 4.80%, respectively. The generated sequences are applied to simple stochastic logic gates and the probability density functions (pdfs) of the outputs are derived. It is shown that these match with the theoretical pdfs of the outputs.

Synthesis of correlated bit streams for stochastic computing

This paper focuses on designing elliptic curve crypto-accelerators in GF(2/sup m/) that are cryptographically scalable and hold some degree of reconfigurability. Previous work in elliptic curve crypto-accelerators focused on implementations using projective coordinate systems for specific field sizes. Their performance, scalar point multiplication per second (kP/s) was determined primarily by the underlying multiplier implementation. In addition, a multiplier only implementation and a multiplier plus divider implementation are compared in terms of critical path, area and area time (AT) product. Our multiplier only design, designed for high performance, can achieve 6314 kP/s for GF(2/sup 571/) and requires 47876 LUTs. Meanwhile our multiplier and divider design, with a greater degree of reconfigurability, can achieve 44 kP/s for GF(2/sup 571/). However, this design requires 27355 LUTs, and has a significantly higher AT product. It is shown that reconfigurability with the reduction polynomial significantly benefits from the addition of a low latency divider unit and scalar point multiplication in affine coordinates. In both cases the performance is limited by a critical path in the control logic.

Keshab K. Parhi

Papers

Interleaved cyclic redundancy check (CRC) code

Loop list scheduler for DSP algorithms under resource constraints

Molecular and DNA Artificial Neural Networks via Fractional Coding

Synthesis of correlated bit streams for stochastic computing

Implementation of scalable elliptic curve cryptosystem crypto-accelerators for GF(2/sup m/)