TY - JOUR
T1 - Analysis of Communication and Network Securities Using the Concepts of Complex Picture Fuzzy Relations
AU - Nasir, Abdul
AU - Jan, Naeem
AU - Khan, Sami Ullah
AU - Gumaei, Abdu
AU - Alothaim, Abdulrahman
N1 - Publisher Copyright:
© 2021 Abdul Nasir et al.
PY - 2021
Y1 - 2021
N2 - In our lives, we cannot avoid the uncertainty. Randomness, rough knowledge, and vagueness lead us to uncertainty. In mathematics, the fuzzy set (FS) theory and logics are used to model uncertain events. This article defines a new concept of complex picture fuzzy relation (CPFR) in the field of FS theory. In addition, the types of CPFRs are also discussed to make the paper more fruitful. Today's complex network architecture faces the ever-changing threats. The cyber-attackers are always trying to discover, catch, and exploit the weaknesses in the networks. So, the security measures are essential to avoid and dismantle such threats. The CPFR has a vast structure composed of levels of membership, abstinence, and nonmembership which models uncertainty better than any other structures in the theory. Moreover, a CPFR has the ability to cope with multivariable problems. Therefore, this article proposes modeling techniques based on the complex picture fuzzy information which are used to study the effectiveness and ineffectiveness of different network securities against several threats and cyber-attack practices. Moreover, the strength and preeminence of the proposed methods are verified by studying their comparison with the existing methods.
AB - In our lives, we cannot avoid the uncertainty. Randomness, rough knowledge, and vagueness lead us to uncertainty. In mathematics, the fuzzy set (FS) theory and logics are used to model uncertain events. This article defines a new concept of complex picture fuzzy relation (CPFR) in the field of FS theory. In addition, the types of CPFRs are also discussed to make the paper more fruitful. Today's complex network architecture faces the ever-changing threats. The cyber-attackers are always trying to discover, catch, and exploit the weaknesses in the networks. So, the security measures are essential to avoid and dismantle such threats. The CPFR has a vast structure composed of levels of membership, abstinence, and nonmembership which models uncertainty better than any other structures in the theory. Moreover, a CPFR has the ability to cope with multivariable problems. Therefore, this article proposes modeling techniques based on the complex picture fuzzy information which are used to study the effectiveness and ineffectiveness of different network securities against several threats and cyber-attack practices. Moreover, the strength and preeminence of the proposed methods are verified by studying their comparison with the existing methods.
UR - http://www.scopus.com/inward/record.url?scp=85118929340&partnerID=8YFLogxK
U2 - 10.1155/2021/9427492
DO - 10.1155/2021/9427492
M3 - Article
C2 - 34754304
AN - SCOPUS:85118929340
SN - 1687-5265
VL - 2021
JO - Computational Intelligence and Neuroscience
JF - Computational Intelligence and Neuroscience
M1 - 9427492
ER -