A Fuzzy Based MCDM Methodology for Risk Evaluation of Cyber Security Technologies

Erdoğan, Melike; Karaşan, Ali; Kaya, İ̇hsan; Budak, Ayşenur; Çolak, Murat

doi:10.1007/978-3-030-23756-1_123

Cited by 5 publications

(3 citation statements)

References 12 publications

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“…Fuzzy logic helps to solve the problem of value assignment to some security or property level [31,32]; however, fuzzy cognitive maps can be used to present the interconnectivity of the situation [33]. Meanwhile, multi-criteria decision-making solutions solve the problem of quantitative metrics, composed of multiple criteria [34][35][36]. While most information security risk assessments require security expert's interpretation, the multi-criteria decision making usually is based on weighting some criteria; therefore, together with data gathering solutions, it can be used by non-experts in the security area.…”

Section: Security Risk And/or Security Level Quantitative Estimation Methodsmentioning

confidence: 99%

Educational Organization’s Security Level Estimation Model

et al. 2021

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During the pandemic, distance learning gained its necessity. Most schools and universities were forced to use e-learning tools. The fast transition to distance learning increased the digitalization of the educational system and influenced the increase of security incident numbers as there was no time to estimate the security level change by incorporating new e-learning systems. Notably, preparation for distance learning was accompanied by several limitations: lack of time, lack of resources to manage the information technologies and systems, lack of knowledge on information security management, and security level modeling. In this paper, we propose a security level estimation model for educational organizations. This model takes into account distance learning specifics and allows quantitative estimation of an organization’s security level. It is based on 49 criteria values, structured into an AHP (Analytic Hierarchy Process) tree, and arranged to final security level metric by incorporating experts’ opinion-based criteria importance coefficients. The research proposed a criteria tree and obtained experts’ opinions lead to educational organization security level evaluation model, resulting in one quantitative metric. It can be used to model different situations and find the better alternative in case of security level, without external security experts usage. Use case analysis results and their similarity to security experts’ evaluation are presented in this paper as validation of the proposed model. It confirms the model meets experts-based information security level ranking, therefore, can be used for simpler security modeling in educational organizations.

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Section: Security Risk And/or Security Level Quantitative Estimation Methodsmentioning

confidence: 99%

Educational Organization’s Security Level Estimation Model

et al. 2021

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“…In this research, they applied the AHP model and Complex Proportional Assessment (COPRAS) for ranking digital marketing technologies. Erdoğan et al [12] presented a fuzzy MCDM model to determine the best cyber security technology. Via fuzzy MCDM process, the author also discussed risk factors in the selection processes.…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluation of Digital Marketing Technologies with Fuzzy Linguistic MCDM Methods

Trung

Thanh

2022

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Technology is becoming the tool that changes how people live every day, and the marketing strategies of businesses are also gradually shifting to the industry 4.0 mindset of constant growth and development. Digital marketing has changed human habits of information accessibility, determined their interactions, and witnessed the birth of a variety of new marketing technologies. Marketers are creating digital marketing products and services that enhance the experience for consumers, products, and services that are also delivered through high digital marketing networks. As a result, data sources become more abundant and allow consumers to have more choices. All products, services, technologies, and data are increasingly meeting the needs of consumers, thereby confirming the effectiveness of digital marketing in today’s market. However, the evaluation and selection of digital marketing technology is very complex since it has many conflicting criteria and goals. The multi-criteria decision-making model (MCDM) is a powerful technique widely used for solving this type of problem. Thus, the author proposed a fuzzy linguistic MCDM method for evaluation of digital marketing technologies. After determining the evaluation criteria and alternatives, two MCDM methods, including Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), are used in the evaluation and selection of digital marketing technologies procedure. Finally, an application is present to demonstrate the potential use of the proposed methodology. The main contribution of this study is to propose a Spherical fuzzy MCDM model to support planners and decision makers in the digital marketing technology evaluation and selection processes. A case study is also performed to showcase the feasibility of the proposed approach.

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“…The potential of fuzzy decision making in computer system security has been demonstrated. Its ability to deal with uncertainty is particularly useful for risk assessment [2], [20]. Normal operation conditions of a CPS are a vague concept and detection of abnormal conditions and unstable states can be modelled and inferred using fuzzy systems where partial truth is accommodated.…”

Section: Moving Forwardmentioning

confidence: 99%

Next Generation Resilient Cyber-Physical Systems

Barbeau,

Carle,

Garcia-Alfaro

et al. 2019

Preprint

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A distributed Cyber-Physical Systems (CPS) consists of tightly integrated computing, communication and control technologies. Recent CPS hacking incidents had significant consequences. In such a context, reinforcing their resilience, referring to their capacity to recover from disruptions, is a key challenge. Concretely, it involves the integration of mechanisms to regulate safety, security and recovery from adverse events, including plans deployed before, during and after incidents occur. We envision a paradigm change where an increase of adversarial resources does not translate anymore into higher likelihood of disruptions. Consistently with current system design practices in other areas, employing high safety technologies and protocols, we outline a vision for next generation CPS addressing the resilience challenge leveraging ideas such machine learning, fuzzy decision and quantum computing.

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A Fuzzy Based MCDM Methodology for Risk Evaluation of Cyber Security Technologies

Cited by 5 publications

References 12 publications

Educational Organization’s Security Level Estimation Model

Educational Organization’s Security Level Estimation Model

Evaluation of Digital Marketing Technologies with Fuzzy Linguistic MCDM Methods

Next Generation Resilient Cyber-Physical Systems

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