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Group Decision Making in Information Systems Security Assessment Using Dual Hesitant Fuzzy Set
Author(s) -
Yu Dejian,
Merigó José M.,
Xu Yejun
Publication year - 2016
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.21804
Subject(s) - computer science , dual (grammatical number) , information security , information systems security , fuzzy logic , set (abstract data type) , information security management system , operator (biology) , network security , fuzzy set , information system , computer security , security information and event management , risk analysis (engineering) , management information systems , artificial intelligence , engineering , cloud computing security , business , cloud computing , repressor , operating system , biochemistry , transcription factor , programming language , art , chemistry , literature , electrical engineering , gene
Network information system security has become a global issue since it is related to the economic development and national security. Information system security assessment plays an important role in the development of security solutions. Aiming at this issue, a dual hesitant fuzzy (DHF) group decision‐making (GDM) method was proposed in this paper to assist the assessment of network information system security. A systemic index containing four aspects was established including organization security, management security, technical security, and personnel management security. The DHF group evaluation matrix was constructed based on the individual evaluation information from each expert. Some power average operator–based DHF information aggregation operators are proposed and used to fusion the performance of each criterion for information systems. The advantage of these operators is that they can describe the relationship between the indexes quantitatively. Finally, a case study about information systems security assessment was presented to verify the effectiveness of proposed GDM methods.