Risk assessment optimization for decision support using intelligent model based on fuzzy inference renewable rules

Abstract

Due to the unreliability of wired communications and the risks of controlling the process of transmitting data besides the complications that affecting data protection and the high costs of systems infrastructure, led to use wireless communications instead of wires media, but these networks are vulnerable towards illegal attacks. The side effects of these attacks are modifying data or penetrate the security system and discover its weaknesses, which leads to great material losses. These risks and difficulties led to the reluctance of wires communications and propose intelligent techniques and robust encryption algorithms for preventing data transmitted over wireless networks to keep it safe from cyber security attacks. So, there is a persistent need for providing intelligent techniques and robust algorithms to preserve conveyed information using wireless network. This paper introduces scenario for proposing intelligent technique to increase data reliability and provides a new way to improve high level of protection besides reduces infrastructure cost. The proposed system relies on two models, where the first model based on producing a knowledge base of risk rules while the aim of the second module is a risk assessment outcomes and encryption process according to attacks type. In this system, reducing risks levels based on renewable rules whereas a novel security system established on non-periodic keys with unsystematic operations using fuzzy system. We concluded that the proposed system has the ability to protect the transmitted data, increases its reliability and reduce the potential risks. MATLAB Toolkit 2014 then Weka open source package was used in encryption and data mining for the proposed system.<iframe class="ginger-extension-definitionpopup" style="left: -91.5px; top: -78px; z-index: 100001; display: none;" src="chrome-extension://kdfieneakcjfaiglcfcgkidlkmlijjnh/content/popups/definitionPopup/index.html?title=Abstract&description=a%20concept%20or%20idea%20not%20associated%20with%20any%20specific%20instance"></iframe>

The impact of digitalization on the income of authors of educational products: Analysis of the influence of factors based on fuzzy logic

“…Various mathematical methods are used to work with qualitative or fuzzy indicators. The method of fuzzy inference systems (FIS) is one of them (Zadeh, 1976;Tsekouras, 2016;Hudec, 2016;Bělohlávek et al, 2017;Shankar & Silva, 1995;Zadeh et al, 1992;Shafizade et al, 2010;Shikhlinskaya & Shafizadeh, 2015;Radhi, 2020;Blahun et al, 2020;Zanon et al, 2020;Hernandez-Aguila et al, 2021;Čičak & Vašiček, 2019;Malyarets et al, 2019). This system was proposed in 1975 by Ebhasim Mamdani, and the method allows you to determine the dependence using both quantitative and qualitative indicators, as well as fuzzy indicators.…”

“…In the analysis, we have used data that is publicly available to the State Statistics Committee and is shown in the table below. We have applied the fuzzy inference logic method for defining the revenue of the person producing the digital educational product (Shafizade et al, 2010;Shikhlinskaya & Shafizadeh, 2015;Leonenkov, 2003;Radhi, Functional blocks of fuzzy inference systems (FIS) (Zadeh, 1976;Tsekouras, 2016;Hudec, 2016;Shafizade et al, 2010;Shikhlinskaya & Shafizadeh, 2015) are:…”

Risk Assessment and Policy Recommendations for a Floating Solar Photovoltaic (FSPV) System

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