Intelligent Automated Intrusion Response System based on fuzzy decision making and risk assessment

2016 ◽  
Author(s):  
Samaneh Berenjian ◽  
Mehdi Shajari ◽  
Nadieh Farshid ◽  
Majid Hatamian
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Intrusion Response ◽  
Response System ◽  
Intrusion Response System

scholarly journals A novel fuzzy risk matrix based risk assessment approach

Kybernetes ◽  
2018 ◽  
Vol 47 (9) ◽  
pp. 1721-1751 ◽  
Author(s):  
Gülin Feryal Can ◽  
Pelin Toktas
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Dynamic Structure ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Risk Matrix ◽  
Content Type ◽  
Second Stage ◽  
Third Stage ◽  
Assessment Approach

Purpose Traditional risk assessment (RA) methodologies cannot model vagueness in risk and cannot prioritize corrective-preventive measures (CPMs) by considering effectiveness of those on risk types (RTs). These cannot combine and reflect accurately different subjective opinions and cannot be used in a linguistic manner. Risk factors (RFs) are assumed to have the same importance and interrelations between RFs are not considered. This study aims to overcome these disadvantages by combining fuzzy logic with multi-criteria decision-making in a dynamic manner. Design/methodology/approach This study proposes a novel three-stage fuzzy risk matrix-based RA integrating fuzzy decision-making trial and evaluation laboratory (F-DEMATEL) and fuzzy multi-attributive border approximation area comparison (F-MABAC). At the first stage, importance weights of RFs are computed by F-DEMATEL. At the second stage, risk degrees of RTs are computed via using fuzzy risk matrix. At the third stage, CPMs are ranked by F-MABAC. Finally, a numerical example for RA in a warehouse is given. Findings Results show that developing instructions for material loading or unloading is the most important CPM and severity is the most important RF for the warehouse. Originality/value This study has originality in terms of having fuzzy dynamic structure. At first, RFs are assumed to be criteria sets then, RTs are assumed to be criteria set considering their risk degrees to rank CPMs in a fuzzy manner. Risk degrees of RTs are used for weights of RTs and effectiveness of CPMs are used for performance values of CPMs.

Dual hesitant fuzzy decision making in optimization models

2021 ◽  
Vol 154 ◽  
pp. 107103
Author(s):  
Fanyong Meng ◽  
Jie Tang ◽  
Witold Pedrycz
Keyword(s):  
Decision Making ◽  
Optimization Models ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision
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