Fuzzy Evaluation of Network Vulnerability

Abstract

Vulnerability of networks is not only associated with the ability to resist disturbances but also has an impact on stable development of the networks in the long run. In this paper, a new vulnerability evaluation based on fuzzy logics is proposed. To obtain the vulnerability of the networks, fuzzy logic is utilized to model uncertain environment. Therefore, this evaluation can be divided into two steps. One is to use a graph to represent the network and analyze the main properties of the network, including average path length, edge betweenness, degree, and clustering coefficient. The other is to use fuzzy logics according to the main properties. Namely, this step is to calculate deviations, design rule database, and obtain vulnerability. Two examples are given to show the efficiency and practicability of the proposed method at the end. Copyright © 2015 John Wiley & Sons, Ltd.

Location of Facility Based on Simulated Annealing and “ZKW” Algorithms

“…(17) Calculate Δ = NewPlanCost − NowPlanCost. (18) if (Δ < 0) then (19) NowPlan = NewPlan; (20) else (21) Calculate exp(−Δ / ) and Generate a random number. (22) if (exp(−Δ / ) > random) then (23) NowPlan = NewPlan; (24) end if (25) end if (26) ( ) − −; (27) end while//inner circulation (28) = /(1 + * ); //Cool down the temperature.…”

“…The goal of this problem is to find optimal locations to build facilities so that the solution of the problem can serve the consumers or clients with the least cost. Generally, the facility location problem could be divided into median problem [2,3], covering problem [4][5][6][7], center problem [8][9][10], multiproduct problem [11,12], dynamic location problem [13,14], multiobjective location problem [15][16][17], competitive problem [18,19], network reliability problem [20,21], and network center location problem [22,23].…”

A novel computation for predicting time series using fuzzy logical distance connectivity function and visibility graph theory

“…By and by, because of the way that vulnerabilities exist unavoidably, incorrect estimations happen from time to time. Inspired by GET, analysts have overseen vulnerabilities in crisis administration [7] human unwavering quality [8] and etymological basic leadership [8]. Another doable hypothesis to adapt to vulnerabilities is fuzzy rationale that is first proposed by Zadeh.…”

Mining Important Nodes in Directed Weighted Complex Networks

“…Since there are many factors to identify the influential nodes, this issue can be seen as a multiattribute decision making model (MADM) [25,26]. Many MADM methods, such as fuzzy sets [27] and evidence theory [28,29], are widely used to ranking the nodes in complex networks [30]. The author gave a new definition on important degree of weighted nodes.…”