Risk assessment is generally performed using models and model is a function of some parameters which are usually affected by uncertainty.
Alborzi Abstract Strong adaptive control can be exercised even without access to accurate data inputs. Such control is possible through fuzzy mathematics, which is a meta-collection of Boolean logic principles that imply relative accuracy.
Fuzzy mathematics find applications in e-commerce, where different risk analysis methods are available for risk assessment and estimation.
Such approaches can be quantitative or qualitative, depending on the type of examined data. Quantitative methods are grounded in statistics, whereas qualitative methods are based on expert judgments and fuzzy set theory.
Given that qualitative methods are very subjective and deal with vague or inaccurate data, fuzzy logic can be used to extract useful information from data inaccuracies. In this study, a model based on the opinions of e-commerce security experts was designed and implemented by using fuzzy expert systems and MATLAB.
A case study was conducted to validate the effectiveness of the Model.
Keywords fuzzy logic; risk assessment system; e-commerce; expert system Full Text: Darlington, The essence of expert systems, Prentice Hall, A. Applications, Methodology, Technology, Vol. Kian university press, N.of the major tools used for security analysis.
Fuzzy systems are Also for software, a rule based fuzzy expert system is used to analyze the risk associated with software Cyber Security Risk Assessment Using Multi Fuzzy Inference System Hany Sallam.
ISSN: Using Fuzzy Logic to Increase the Accuracy of E-Commerce Risk Assessment Based on an Expert System Strong adaptive control can be exercised even without access to accurate data inputs.
Such control is possible through fuzzy mathematics, which is a meta-collection of Boolean logic principles that imply relative accuracy.
PSR (fuzzy-based function point analysis with performance metrics, security, and reliability factors)  algorithm that has been proposed for improving the accuracy of the software. Beginning with a short overview of how security system performance fits within an overall security risk analysis frame-work, this paper presents the basic concepts of fuzzy systems and applies them to develop a model that approximates the true relationship between defensive capabilities and probability of adversary success.
A New Fuzzy Risk Analysis Method based on Generalized Fuzzy Numbers Xiaoyan Su1,2,3 1Key Laboratory of Digital Agricultural Early-warning Technology, Ministry of Agriculture of China, Beijing, China 2 Hangzhou Key Lab of E-Business and Information Security, Hangzhou Normal University, Zhejiang, China 3School of Electronics & Information Technology, Shanghai Jiao Tong University, .
fuzzy owa model for information security risk management21 of a decisionmaking person and the interaction between criteria in comparison with other multicriteria decision making methods, including the analytic hierarchy process (AHP) , and the technique of.