PurposeNatural disasters cause serious operational risks and disruptions, which further impact the food supply in and around the disaster-impacted area. resilient functions in the supply chain are required to absorb t...
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PurposeNatural disasters cause serious operational risks and disruptions, which further impact the food supply in and around the disaster-impacted area. resilient functions in the supply chain are required to absorb the impact of resultant disruptions in perishable food supply chains (FSC). The present study identifies specific resilient functions to overcome the problems created by natural disasters in the FSC ***/methodology/approachThe quality function deployment (QFD) method is utilized for identifying these relations. Further, fuzzy term sets and the analytical hierarchy process (AHP) are used to prioritize the identified problems. The results obtained are employed to construct a QFD matrix with the solutions, followed by the technique for order of preference by similarity to the ideal solution (TOPSIS) on the house of quality (HOQ) matrix between the identified problems and *** results from the study reflect that the shortage of employees in affected areas is the major problem caused by a natural disaster, followed by the food movement problem. The results from the analysis matrix conclude that information sharing should be kept at the highest priority by policymakers to build and increase resilient functions and sustainable crisis management in a perishable FSC ***/valueThe study suggests practical implications for managing a FSC crisis during a natural disaster. The unique contribution of this research lies in finding the correlation and importance ranking among different resilience functions, which is crucial for managing a FSC crisis during a natural disaster.
In this correspondence, we present a number of methods for constructing new resilient functions from old ones, These methods are significant generalizations of some previously known methods. The nonlinearity of some n...
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In this correspondence, we present a number of methods for constructing new resilient functions from old ones, These methods are significant generalizations of some previously known methods. The nonlinearity of some new constructed resilient functions is also discussed.
The design of n-variable t-resilient functions with strictly almost optimal (SAO) nonlinearity (> 2(n-1) - 2(n/2), n even) appears to be a rather difficult task. The known construction methods commonly use a rather...
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The design of n-variable t-resilient functions with strictly almost optimal (SAO) nonlinearity (> 2(n-1) - 2(n/2), n even) appears to be a rather difficult task. The known construction methods commonly use a rather large number (exactly Sigma(n/2)(i=t+1)((n/2)(i))) of affine subfunctions in n/2 variables which can induce some algebraic weaknesses, making these functions susceptible to certain types of guess and determine cryptanalysis and dynamic cube attacks. In this paper, the concept of non-overlap spectra functions is introduced, which essentially generalizes the idea of disjoint spectra functions on different variable spaces. Two, general methods to obtain a large set of non-overlap spectra functions are given and a new framework for designing infinite classes of resilient functions with SAO nonlinearity is developed based on these. Unlike previous construction methods, our approach employs only a few n/2-variable affine subfunctions in the design, resulting in a more favourable algebraic structure. It is shown that these new resilient SAO functions properly include all the existing classes of resilient SAO functions as a subclass. Moreover, it is shown that the new class provides a better resistance against (fast) algebraic attacks than the known functions with SAO nonlinearity, and in addition these functions are more robust to guess and determine cryptanalysis and dynamic cube attacks. (C) 2017 Elsevier Inc. All rights reserved.
In this paper, we provide a new generalized construction method for highly nonlinear t-resilient functions, F: F-2(n) --> F-2(m). The construction is based on the use of linear error-correcting codes together with ...
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In this paper, we provide a new generalized construction method for highly nonlinear t-resilient functions, F: F-2(n) --> F-2(m). The construction is based on the use of linear error-correcting codes together with highly nonlinear multiple output functions. Given a linear [u, m, t + 1] code we show that it is possible to construct n-variable, m-output, t-resilient functions with very high nonlinearity for n > u. The method provides the currently best known nonlinearity results for most of the cases.
Orthogonal arrays (OAs) are basic combinatorial structures, which appear under various disguises in cryptology and the theory of algorithms. Among their applications are universal hashing, authentication codes, resili...
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Orthogonal arrays (OAs) are basic combinatorial structures, which appear under various disguises in cryptology and the theory of algorithms. Among their applications are universal hashing, authentication codes, resilient and correlation-immune functions, derandomization of algorithms, and perfect local randomizers. In this paper, we give new explicit bounds on the size of orthogonal arrays using Delsarte's linear programming method. Specifically, we prove that the minimum number of rows in a binary orthogonal array of length n and strength t is at least 2(n) - (n2(n-1)/t+1) and also at least 2(n) - (2(n-2)(n+1)/[t+1/2]). We also prove that these bounds are as powerful as the linear programming bound itself for many parametric situations. An (n, m, t)-resilient function is a function f : {0, 1}(n) --> {0, 1}(m) such that every possible output m-tuple is equally likely to occur when the values of t arbitrary inputs are fixed by an opponent and the remaining n-t input bits are chosen independently at random. A basic problem is to maximize t given m and n, i.e., to determine the largest value of t such that an (n, m, t)-resilient function exists. In this paper, we obtain upper and lower bounds for the optimal values of t where 1 less than or equal to n less than or equal to 25 and 1 less than or equal to m < n. The upper bounds are derived from Delsarte's linear programming bound, and the lower bounds come from constructions based on error-correcting codes. We also obtain new explicit upper bounds for the optimal values of t. It was proved by Chor et al. in [Proc. 26th IEEE Symp. on Foundations of Computer Science, 1985, pp. 396-407] that an (n,2,t)-resilient function exists if and only if t < [2n/3]. This result was generalized by Friedman [Proc. 33rd IEEE Symp. on Foundations ol Computer Science, 1992, pp. 314-319], who proved a bound for general m. We also prove some new bounds, and complete the determination of the optimal resiliency of resilient functions with m =
This correspondence studies resilient functions which have applications in fault-tolerant distributed computing, quantum cryptographic key distribution, and random sequence generation for stream ciphers. We present a ...
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This correspondence studies resilient functions which have applications in fault-tolerant distributed computing, quantum cryptographic key distribution, and random sequence generation for stream ciphers. We present a number of new methods for synthesizing resilient functions. An interesting aspect of these methods is that they are applicable both to linear and nonlinear resilient functions. Our second major contribution is to show that every Linear resilient function can be transformed into a Large number of nonlinear resilient functions with the same parameters. As a result, we obtain resilient functions that are highly nonlinear and have a high algebraic degree.
We extend the notions of correlation-immune functions and resilient functions to functions over any finite alphabet. A previous result due to Gopalakrishnan and Stinson is generalized as we give an orthogonal array ch...
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We extend the notions of correlation-immune functions and resilient functions to functions over any finite alphabet. A previous result due to Gopalakrishnan and Stinson is generalized as we give an orthogonal array characterization, a Fourier transform and a matrix characterization for correlation-immune and resilient functions over any finite alphabet endowed with the structure of an Abelian group. We then point out the existence of a tradeoff between the degree of the algebraic normal form and the correlation-immunity order of any function defined on a finite field and we construct some infinite families of t-resilient functions with optimal nonlinearity which are particularly well-suited for combining linear feedback shift registers. We also point out the link between correlation-immune functions and some cryptographic objects as perfect local randomizers and multipermutations.
Using a heuristic search technique, several examples for 9-variable Boolean functions with nonlinearity, 240, algebraic degree 5, and resiliency degree 3 were constructed. This construction affirmatively answers the o...
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Using a heuristic search technique, several examples for 9-variable Boolean functions with nonlinearity, 240, algebraic degree 5, and resiliency degree 3 were constructed. This construction affirmatively answers the open problem about the existence of such functions.
Using a heuristic search combined with some algebraic techniques, several examples for 10-variable Boolean functions with nonlinearity 488, algebraic degree 7, and resiliency degree 2, were constructed. This construct...
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Using a heuristic search combined with some algebraic techniques, several examples for 10-variable Boolean functions with nonlinearity 488, algebraic degree 7, and resiliency degree 2, were constructed. This construction affirmatively answers the open problem about the existence of such functions.
Bastd on the relationship between nonlinearity and resiliency of amulti-output function, we present a method for constructing noninterseeling linear codes frompacking design. Through these linear codes, we obtain n-va...
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Bastd on the relationship between nonlinearity and resiliency of amulti-output function, we present a method for constructing noninterseeling linear codes frompacking design. Through these linear codes, we obtain n-variable, m-output, t-resilient functionswith very high nonlinearity. Their nonlinearities are currently the best results for most of cases.
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