• 제목/요약/키워드: polynomial basis

검색결과 232건 처리시간 0.02초

A Group Key Management Scheme for WSN Based on Lagrange Interpolation Polynomial Characteristic

  • Wang, Xiaogang;Shi, Weiren;Liu, Dan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권7호
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    • pp.3690-3713
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    • 2019
  • According to the main group key management schemes logical key hierarchy (LKH), exclusion basis systems (EBS) and other group key schemes are limited in network structure, collusion attack, high energy consumption, and the single point of failure, this paper presents a group key management scheme for wireless sensor networks based on Lagrange interpolation polynomial characteristic (AGKMS). That Chinese remainder theorem is turned into a Lagrange interpolation polynomial based on the function property of Chinese remainder theorem firstly. And then the base station (BS) generates a Lagrange interpolation polynomial function f(x) and turns it to be a mix-function f(x)' based on the key information m(i) of node i. In the end, node i can obtain the group key K by receiving the message f(m(i))' from the cluster head node j. The analysis results of safety performance show that AGKMS has good network security, key independence, anti-capture, low storage cost, low computation cost, and good scalability.

GF($2^n$) 위에서의 다항식 일수분해 (The polynomial factorization over GF($2^n$))

  • 김창한
    • 정보보호학회논문지
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    • 제9권3호
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    • pp.3-12
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    • 1999
  • 공개키 암호법은 정수 인수분해의 어려움에 바탕을 둔 RSA와 이산대수문제의 어려움에 근거한 EIGamal 암호법을 대표된다. GF(qn)*에서 index-calculus 이산대수 알고리즘을 다항식 인수분해를 필요로 한다. 최근에 Niederreiter에 의하여 유한체위에서의 다항식 인수분해 알고리즘이 제안되었다. 이 논문에서는 정규기저(normal basis)를 이용한 유한체의 연산을 c-언어로 구현하고, 이것을 이용한 Niederreiter의 알고리즘을 기반으로 유한체위에서의 다항식 인수분해 알고리즘과 구현한 결과를 제시한다. The public key crytptosystem is represented by RSA based on the difficulty of integer factorization and ElGamal cryptosystem based on the intractability of the discrete logarithm problem in a cyclic group G. The index-calculus algorithm for discrete logarithms in GF(qn)* requires an polynomial factorization. The Niederreiter recently developed deterministic facorization algorithm for polynomial over GF(qn) In this paper we implemented the arithmetic of finite field with c-language and gibe an implementation of the Niederreiter's algorithm over GF(2n) using normal bases.

Polynomial Fuzzy Radial Basis Function Neural Network Classifiers Realized with the Aid of Boundary Area Decision

  • Roh, Seok-Beom;Oh, Sung-Kwun
    • Journal of Electrical Engineering and Technology
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    • 제9권6호
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    • pp.2098-2106
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    • 2014
  • In the area of clustering, there are numerous approaches to construct clusters in the input space. For regression problem, when forming clusters being a part of the overall model, the relationships between the input space and the output space are essential and have to be taken into consideration. Conditional Fuzzy C-Means (c-FCM) clustering offers an opportunity to analyze the structure in the input space with the mechanism of supervision implied by the distribution of data present in the output space. However, like other clustering methods, c-FCM focuses on the distribution of the data. In this paper, we introduce a new method, which by making use of the ambiguity index focuses on the boundaries of the clusters whose determination is essential to the quality of the ensuing classification procedures. The introduced design is illustrated with the aid of numeric examples that provide a detailed insight into the performance of the fuzzy classifiers and quantify several essentials design aspects.

다항식 변형률 분포함수를 이용한 철근콘크리트 인장부재의 균열해석 (Cracking Analysis of RC Tension Members Using Polynomial Strain Distribution Function)

  • 곽효경;송종영
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2001년도 봄 학술발표회 논문집
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    • pp.267-274
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    • 2001
  • In this paper, a analytical model which can simulate the post-cracking behavior and tension stiffening effect in a reinforced concrete(RC) tension member is proposed. Unlike the classical approaches using the bond stress-slip relationship or the assumed bond stress distribution, the tension stiffening effect at post-cracking stage is quantified on the basis of polynomial strain distribution functions of steel and concrete, and its contribution is implemented into the reinforcing steel. The introduced model can be effectively used in constructing the stress-strain curve of concrete at post-cracking stage, and the loads carried by concrete and by reinforcing steel along the member axis can be directly evaluated on the basis of the introduced model. In advance, the prediction of cracking loads and elongations of reinforced steel using the introduced model shows good agreements with results from previous analytical studies and experimental data.

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3X Serial GF(2$^m$) Multiplier on Polynomial Basis

  • Moon, San-Gook
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2005년도 춘계종합학술대회
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    • pp.928-930
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    • 2005
  • With an increasing importance of the information security issues, the efficienct calculation process in terms of finite field level is becoming more important in the Elliptic curve cryptosystems. Serial multiplication architectures are based on the Mastrovito's serial multiplier structure. In this paper, we manipulate the numerical expressions so that we could suggest a 3-times as fast as (3x) the Mastrovito's multiplier using the polynomial basis. The architecture was implemented with HDL, to be evaluated and verified with EDA tools. The implemented 3x GF (Galois Field) multiplier showed 3 times calculation speed as fast as the Mastrovito's, only with the additional partial-sum generation processing unit.

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내부점 선형계획법에서의 최적기저 추출방법의 구현 (On the Implementation of an Optimal Basis Identification Procedure for Interior Point Method)

  • 임성묵;박순달
    • 경영과학
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    • 제17권2호
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    • pp.1-12
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    • 2000
  • In this study, we deals with the implementation of an optimal basis identification procedure for interior point methods. Our implementation is based on Megiddo’s strongly polynomial algorithm applied to Andersen and Ye’s approximate LP construction. Several techniques are explained such as the use of effective indicator for obtaining optimal partition when constructing the approximate LP, the efficient implementation of the problem reduction technique proposed by Andersen, the crashing procedure needed for fast dual phase of Megiddo’s algorithm and the construction of the stable initial basis. By experimental comparison, we show that our implementation is superior to the crossover scheme implementation.

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최적화된 pRBF 뉴럴 네트워크에 의한 정적 상황 인지 시스템에 관한 연구 (A Study on Static Situation Awareness System with the Aid of Optimized Polynomial Radial Basis Function Neural Networks)

  • 오성권;나현석;김욱동
    • 전기학회논문지
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    • 제60권12호
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    • pp.2352-2360
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    • 2011
  • In this paper, we introduce a comprehensive design methodology of Radial Basis Function Neural Networks (RBFNN) that is based on mechanism of clustering and optimization algorithm. We can divide some clusters based on similarity of input dataset by using clustering algorithm. As a result, the number of clusters is equal to the number of nodes in the hidden layer. Moreover, the centers of each cluster are used into the centers of each receptive field in the hidden layer. In this study, we have applied Fuzzy-C Means(FCM) and K-Means(KM) clustering algorithm, respectively and compared between them. The weight connections of model are expanded into the type of polynomial functions such as linear and quadratic. In this reason, the output of model consists of relation between input and output. In order to get the optimal structure and better performance, Particle Swarm Optimization(PSO) is used. We can obtain optimized parameters such as both the number of clusters and the polynomial order of weights connection through structural optimization as well as the widths of receptive fields through parametric optimization. To evaluate the performance of proposed model, NXT equipment offered by National Instrument(NI) is exploited. The situation awareness system-related intelligent model was built up by the experimental dataset of distance information measured between object and diverse sensor such as sound sensor, light sensor, and ultrasonic sensor of NXT equipment.

Efficient Semi-systolic AB2 Multiplier over Finite Fields

  • Kim, Keewon
    • 한국컴퓨터정보학회논문지
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    • 제25권1호
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    • pp.37-43
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    • 2020
  • 본 논문에서는 유한체상의 SPB(shifted polynomial basis)를 사용한 효율적인 AB2 곱셈 알고리즘을 제안한다. SPB의 특징을 이용하여, AB2 곱셈을 위한 수식을 두 부분으로 분할하였다. 분할된 두 수식은 동시에 실행가능하며, 이를 병렬로 처리하는 알고리즘을 도출하였다. 그리고 제안한 알고리즘을 기반으로 효율적인 세미-시스톨릭(semi-systolic) AB2 곱셈기를 제안한다. 제안한 곱셈기는 기존의 곱셈기에 비해 낮은 공간-시간 복잡도(area-time complexity)를 가진다. 기존의 구조들과 비교하면, 제안한 AB2 곱셈기는 공간-시간 복잡도면에서 Wei, Wang-Guo, Kim-Lee, 및 Choi-Lee의 곱셈기들의 약 94%, 87%, 86%, 및 83% 가량이 감소되었다. 따라서 제안한 곱셈기는 VLSI(very large scale integration) 구현에 적합하며 다양한 응용의 기초적인 구성 요소로 쉽게 적용할 수 있다.

Basis Translation Matrix between Two Isomorphic Extension Fields via Optimal Normal Basis

  • Nogami, Yasuyuki;Namba, Ryo;Morikawa, Yoshitaka
    • ETRI Journal
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    • 제30권2호
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    • pp.326-334
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    • 2008
  • This paper proposes a method for generating a basis translation matrix between isomorphic extension fields. To generate a basis translation matrix, we need the equality correspondence of a basis between the isomorphic extension fields. Consider an extension field $F_{p^m}$ where p is characteristic. As a brute force method, when $p^m$ is small, we can check the equality correspondence by using the minimal polynomial of a basis element; however, when $p^m$ is large, it becomes too difficult. The proposed methods are based on the fact that Type I and Type II optimal normal bases (ONBs) can be easily identified in each isomorphic extension field. The proposed methods efficiently use Type I and Type II ONBs and can generate a pair of basis translation matrices within 15 ms on Pentium 4 (3.6 GHz) when $mlog_2p$ = 160.

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선형계획문제의 강성다항식 계산단계 기법에 관한 연구 (A Study on the Strong Polynomial Time Algorithm for the Linear Programming)

  • 정성진;강완모;정의석;허홍석
    • 대한산업공학회지
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    • 제19권4호
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    • pp.3-11
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    • 1993
  • We propose a new dual simplex method using a primal interior point. The dropping variable is chosen by utilizing the primal feasible interior point. For a given dual feasible basis, its corresponding primal infeasible basic vector and the interior point are used for obtaining a decreasing primal feasible point The computation time of moving on interior point in our method takes much less than that od Karmarker-type interior methods. Since any polynomial time interior methods can be applied to our method we conjectured that a slight modification of our method can give a polynomial time complexity.

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