Evaluating the Impact of Malware Analysis Techniques for Securing Web Applications through a Decision-Making Framework under Fuzzy Environment

Kumar, Rajeev; Alenezi, Mamdouh; Ansari, Md Tarique Jamal; Gupta, Bineet Kumar; Agrawal, Alka; Khan, Raees Ahmad

doi:10.22266/ijies2020.1231.09

Cited by 23 publications

(27 citation statements)

References 44 publications

(64 reference statements)

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“…2 The hierarchical levels were prepared to control the variables and determine the outcomes. With the help of [28][29][30][31][32][33], the fuzzy-aggregated pair-wise comparison matrix at level 1 was developed, as shown in Tab. 1.…”

Section: Resultsmentioning

confidence: 99%

“…During this MCDM process, experts, academicians and researchers have established and assessed the evaluation practices, barriers and solutions for efficient malicious traffic detection system through the literature evaluations in which the established barriers and solutions are shown. Saaty [42] introduced the Analytic Hierarchy Process (AHP) which is considered to be one of the most important and efficient methods for addressing difficult multiple criteria decision-making [28,29,30,31,32]. However, there are some constraints in the use of the AHP, like an inconsistent judgmental reach and the lack of ambiguity.…”

Section: Fuzzy Ahp-topsismentioning

confidence: 99%

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Integrated Fuzzy Based Computational Mechanism for the Selection of Effective Malicious Traffic Detection Approach

Almotiri

2021

IEEE Access

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A mechanism to effectively detect malicious traffic in the present context where new cyber criminals and threatening actors are emerging every day, has become a compelling need. These invaders use overwhelming tactics that mask the nature of attacks and make bad acts seem innocuous. A growing number of trustworthy electronic systems and facilities have been introduced with the fast development of pervasive digital technologies. However threats to cyber-security continue to grow, posing hindrance in the efficient use of digital services. The detection and classification of malicious traffic due to security threats can be done by an efficacious traffic detection approach. The development of a smart, precise malicious traffic detection system has therefore become a subject of extensive research. Current traffic detection systems are typically employed in conventional network traffic detection. These systems sometimes face failure and cannot recognize many known or modern security threats. This is because they rely on conventional algorithms which focus less on precise selection and classification of functions. As a result, several well-known traffic signatures remain unidentified and latent. Hence, there is a need to evaluate each significant malicious traffic detection system based on the performance of the system. In this research work, the author has used the Fuzzy AHP methodology which is designed to address the issues related to the vagueness, uncertainties and total awareness of languages. In addition, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was implemented in order to assess the order of preference. Furthermore, the Multi-Criteria Decision-Making (MCDM) method was used for classifying the impact of the alternatives according to their overall performance. The study's conclusive evaluations will be a corroborative reference for the practitioners working in the domain of assessing and selecting the most effective traffic detection approach for more reliable, efficient and systematic design.

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Section: Resultsmentioning

confidence: 99%

Section: Fuzzy Ahp-topsismentioning

confidence: 99%

Integrated Fuzzy Based Computational Mechanism for the Selection of Effective Malicious Traffic Detection Approach

Almotiri

2021

IEEE Access

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“…TOPSIS procedure 's implementation is an advanced approach. Hence, most of its application scenarios to overcome multiple issues represent the overall trends and developments of all MCDM approaches to solve relatively complex assignments [24]. The strongest ideal solution, as per this technique, would be something which is very close to the positive-ideal solution (PIS), and the furthest from the negative-ideal solution (NIS).…”

Section: Topsis Methodsmentioning

confidence: 99%

A Multi-Perspective Benchmarking Framework for Estimating Usable-Security of Hospital Management System Software Based on Fuzzy Logic, ANP and TOPSIS Methods

2021

KSII TIIS

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One of the biggest challenges that the software industry is facing today is to create highly efficient applications without affecting the quality of healthcare system software. The demand for the provision of software with high quality protection has seen a rapid increase in the software business market. Moreover, it is worthless to offer extremely user-friendly software applications with no ideal security. Therefore a need to find optimal solutions and bridge the difference between accessibility and protection by offering accessible software services for defense has become an imminent prerequisite. Several research endeavours on usable security assessments have been performed to fill the gap between functionality and security. In this context, several Multi-Criteria Decision Making (MCDM) approaches have been implemented on different usability and security attributes so as to assess the usable-security of software systems. However, only a few specific studies are based on using the integrated approach of fuzzy Analytic Network Process (FANP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) technique for assessing the significant usable-security of hospital management software. Therefore, in this research study, the authors have employed an integrated methodology of fuzzy logic, ANP and TOPSIS to estimate the usablesecurity of

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“…The battery in these vehicles must be charged at regular intervals, often by connecting them to a charging station. One of the most significant barriers to BEV acceptance is "range anxiety" [26][27][28][29][30][31][32][33], which occurs when owners are concerned about being stuck in the middle of the highway with a completely depleted battery [17,18]. BEVs are capable of transforming about 80% of the power stored in the batteries into action.…”

Section: Battery Electric Vehicles (Bevs)mentioning

confidence: 99%

Toward a Unified Model Approach for Evaluating Different Electric Vehicles

et al. 2021

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Considering rising pollution as well as fuel expenses, it has now become critical to transition to a sustainable method of transportation. As a result, automakers have begun to spend on research and development in the electric vehicle (EV) industry. The amount of EVs has expanded rapidly in recent years. This is owing to new improved technology, particularly in electric motor engineering, as well as government initiatives to limit the level of environmental impact produced by combustion engines. Because EVs are powered by electricity, implementing their charging stations presents certain complications. In this paper, we have discussed the different types of EVs, such as BEVs, FCEVs, HEVs, PHEVs, and REHEVs. Even though the capacity of many of these electric car models has been substantially enhanced within the past few years, some challenges remain as a selection barrier for several customers. Considering these challenges, we have also implemented a fuzzy AHP-TOPSIS-based unified model to evaluate the different types of EVs. The study’s technical importance is the identification of various evaluation factors, implementation of a unified model for measuring performance, and computation using the fuzzy MCDM technique. The outcomes of the unified model approach also were validated. We concluded that FCEVs are excellent for long journeys, and have the resources to cause minimal disruption.

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Evaluating the Impact of Malware Analysis Techniques for Securing Web Applications through a Decision-Making Framework under Fuzzy Environment

Cited by 23 publications

References 44 publications

Integrated Fuzzy Based Computational Mechanism for the Selection of Effective Malicious Traffic Detection Approach

Integrated Fuzzy Based Computational Mechanism for the Selection of Effective Malicious Traffic Detection Approach

A Multi-Perspective Benchmarking Framework for Estimating Usable-Security of Hospital Management System Software Based on Fuzzy Logic, ANP and TOPSIS Methods

Toward a Unified Model Approach for Evaluating Different Electric Vehicles

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