An Optimization Model for Appraising Intrusion-Detection Systems for Network Security Communications: Applications, Challenges, and Solutions.

Cyber-attacks are getting increasingly complex, and as a result, the functional concerns of intrusion-detection systems (IDSs) are becoming increasingly difficult to resolve. The credibility of security services, such as privacy preservation, authenticity, and accessibility, may be jeopardized if breaches are not detected. Different organizations currently utilize a variety of tactics, strategies, and technology to protect the systems' credibility in order to combat these dangers. Safeguarding approaches include establishing rules and procedures, developing user awareness, deploying firewall and verification systems, regulating system access, and forming computer-issue management groups. The effectiveness of intrusion-detection systems is not sufficiently recognized. IDS is used in businesses to examine possibly harmful tendencies occurring in technological environments. Determining an effective IDS is a complex task for organizations that require consideration of many key criteria and their sub-aspects. To deal with these multiple and interrelated criteria and their sub-aspects, a multi-criteria decision-making (MCMD) approach was applied. These criteria and their sub-aspects can also include some ambiguity and uncertainty, and thus they were treated using q-rung orthopair fuzzy sets (q-ROFS) and q-rung orthopair fuzzy numbers (q-ROFNs). Additionally, the problem of combining expert and specialist opinions was dealt with using the q-rung orthopair fuzzy weighted geometric (q-ROFWG). Initially, the entropy method was applied to assess the priorities of the key criteria and their sub-aspects. Then, the combined compromised solution (CoCoSo) method was applied to evaluate six IDSs according to their effectiveness and reliability. Afterward, comparative and sensitivity analyses were performed to confirm the stability, reliability, and performance of the proposed approach. The findings indicate that most of the IDSs appear to be systems with high potential. According to the results, Suricata is the best IDS that relies on multi-threading performance.

Intelligent model for contemporary supply chain barriers in manufacturing sectors under the impact of the COVID-19 pandemic.

The COVID-19 pandemic has cast a shadow on the global economy. Since the beginning of 2020, the pandemic has contributed significantly to the global recession. In addition to the health damages of the pandemic, the economic impacts are also severe. The consequences of such effects have pushed global supply chains toward their breaking point. Industries have faced multiple obstacles, threatening the fragile flow of raw materials, spare parts, and consumer goods. Previous studies showed that supply chain barriers have multi-faceted impacts on industries and supply chains, which demand appropriate measures. In this regard, seven major barriers that directly impact industries have been identified to determine which industry is most affected by the COVID-19 pandemic. This paper utilized a hybrid multi-criteria decision-making (MCDM) approach under a neutrosophic environment using trapezoidal neutrosophic numbers to rank those barriers. The Analytical Network Process (ANP) quantifies the effects and considers the interrelationships between the determined barriers (criteria) involved in decision-making. Subsequently, the Measurement Alternatives and Ranking according to the COmpromise Solution (MARCOS) method was adopted to rank six industries according to the impact of those barriers. Results show that the lack of inventory is the largest barrier to influencing industries, followed by the lack of manpower. Sensitivity analysis is performed to detect the change in the rank of industries according to the change in the relative importance of the barriers.

A novel model for evaluation Hospital medical care systems based on plithogenic sets.

This research suggests an approach constructed on the connotation of plithogenic theory and VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) technique to come up with a methodical procedure to assess the infirmary serving under a framework of plithogenic theory, where the ambiguity, incomplete information, qualitative information, approximate evaluation, imprecision and uncertainty are addressed with semantic expressions determined by plithogenic numbers and computing of contradiction degrees of attribute values. This research stratifies the plithogenic multi criteria decision making (MCDM) strategy for defining the significant weights of assessing standards, and the VIKOR technique is applied for enhancing the serving efficiency classifications of the possible substitutes. An experimental issue, including 11 assessing standards, 3 private and 2 general hospitals in Zagazig, has been evaluated by 3 assessors from several areas of medical activities, asked to validate the suggested strategy. In this research, we give some definitions of the plithogenic environment, which is more general and comprehensive than fuzzy, intuitionistic fuzzy and neutrosophic ones. The plithogeny is interested in the contradiction degrees between attribute values that help in better calculating the aggregations. We conducted the data analysis and the results showed us that the serving efficiency of private medical centers is superior than that of general medical centers due to the fact that public medical centers are scarcely supported by governmental institutions. The private medical centers have to ward themselves to keep possession of bringing patients or attract patients. We conducted the sensitivity analysis of the achieved results, to verify their validity, and to find out to what extent the different values affect the ranking of available alternatives.

A Group Decision Making Framework Based on Neutrosophic TOPSIS Approach for Smart Medical Device Selection.

Advances in the medical industry has become a major trend because of the new developments in information technologies. This research offers a novel approach for estimating the smart medical devices (SMDs) selection process in a group decision making (GDM) in a vague decision environment. The complexity of the selected decision criteria for the smart medical devices is a significant feature of this analysis. To simulate these processes, a methodology that combines neutrosophics using bipolar numbers with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) under GDM is suggested. Neutrosophics with TOPSIS approach is applied in the decision making process to deal with the vagueness, incomplete data and the uncertainty, considering the decisions criteria in the data collected by the decision makers (DMs). In this research, the stress is placed upon the choosing of sugar analyzing smart medical devices for diabetics' patients. The main objective is to present the complications of the problem, raising interest among specialists in the healthcare industry and assessing smart medical devices under different evaluation criteria. The problem is formulated as a multi criteria decision type with seven alternatives and seven criteria, and then edited as a multi criteria decision model with seven alternatives and seven criteria. The results of the neutrosophics with TOPSIS model are analyzed, showing that the competence of the acquired results and the rankings are sufficiently stable. The results of the suggested method are also compared with the neutrosophic extensions AHP and MOORA models in order to validate and prove the acquired results. In addition, we used the SPSS program to check the stability of the variations in the rankings by the Spearman coefficient of correlation. The selection methodology is applied on a numerical case, to prove the validity of the suggested approach.