Deep Learning-Based Symptomizing Cyber Threats Using Adaptive 5G Shared Slice Security Approaches

In fifth Generation (5G) networks, protection from internal attacks, external breaches, violation of confidentiality, and misuse of network vulnerabilities is a challenging task. Various approaches, especially deep-learning (DL) prototypes, have been adopted in order to counter such challenges. For 5G network defense, DL module are recommended here in order to symptomize suspicious NetFlow data. This module behaves as a virtual network function (VNF) and is placed along a 5G network. The DL module as a cyber threat-symptomizing (CTS) unit acts as a virtual security scanner along the 5G network data analytic function (NWDAF) to monitor the network data. When the data were found to be suspicious, causing network bottlenecks and let-downs of end-user services, they were labeled as “Anomalous”. For the best proactive and adaptive cyber defense system (PACDS), a logically organized modular approach has been followed to design the DL security module. In the application context, improvements have been made to input features dimension and computational complexity reduction with better response times and accuracy in outlier detection. Moreover, key performance indicators (KPIs) have been proposed for security module placement to secure interslice and intraslice communication channels from any internal or external attacks, also suggesting an adaptive defense mechanism and indicating its placement on a 5G network. Among the chosen DL models, the CNN model behaves as a stable model during behavior analysis in the results. The model classifies botnet-labeled data with 99.74% accuracy and higher precision

Evaluating Usability of Academic Websites through a Fuzzy Analytical Hierarchical Process

In the higher education sector, there is a growing trend to offer academic information to users through websites. Contemporarily, the users (i.e., students/teachers, parents, and administrative staff) greatly rely on these websites to perform various academic tasks, including admission, access to learning management systems (LMS), and links to other relevant resources. These users vary from each other in terms of their technological competence, objectives, and frequency of use. Therefore, academic websites should be designed considering different dimensions, so that everybody can be accommodated. Knowing the different dimensions with respect to the usability of academic websites is a multi-criteria decision-making (MCDM) problem. The fuzzy analytic hierarchy process (FAHP) approach has been considered to be a significant method to deal with the uncertainty that is involved in subjective judgment. Although a wide range of usability factors for academic websites have already been identified, most of them are based on the judgment of experts who have never used these websites. This study identified important factors through a detailed literature review, classified them, and prioritized the most critical among them through the FAHP methodology, involving relevant users to propose a usability evaluation framework for academic websites. To validate the proposed framework, five websites of renowned higher educational institutes (HEIs) were evaluated and ranked according to the usability criteria. As the proposed framework was created methodically, the authors believe that it would be helpful for detecting real usability issues that currently exist in academic websites

A zadirachta indica-assisted green synthesis of magnesium oxide nanoparticles for degradation of Reactive Red 195 dye: a sustainable environmental remedial approach

Abstract A variety of industries employ synthetic azo dyes. However, the biosphere is being damaged by the unused/leftover azo dyes, which pose a danger to all living things. Therefore, treating them to shield the environment from the potential harm of azo dyes is crucial. Bio-sorption is a cheap and effective mode for eliminating toxic dyes in the environment. The current work focused on synthesizing magnesium oxide (MgO) nanoparticles using an aqueous leaf extract of neem (Azadirachta indica). The XRD and SEM analyses of MgO nanoparticles indicated the crystalline nature of MgO nanoparticles with a cubic structure, and the size was around 90–100 nm. FTIR analysis showed the presence of a stretching frequency peak at 550 cm−1, confirming the Mg–O bond. The surface analysis revealed the cluster form of the synthesized nanoparticles. The UV–visible absorption peak for MgO nanoparticles was found at 294 nm and band gap of 4.52 eV. In order to eliminate the Reactive Red 195 dye, MgO nanoparticles were used. At pH 4, 40 °C, 0.02% dye concentration, and 0.003 g/L catalyst amount, the highest degree of decolorization (91%) was seen. Decreased total organic carbon (TOC) and the chemical oxygen demand (COD) percent were 84.33% and 81.3%, respectively. The proposed mechanism of target dye degradation was also investigated. MgO NPs were found to be effective in their catalytic behavior toward the degradation of Reactive Red 195 dye up to five cycles with almost no change in their catalytic activity

Nonwoven/Nanomembrane Composite Functional Sweat Pads

Sweat is a natural body excretion produced by skin glands, and the body cools itself by releasing salty sweat. Wetness in the underarms and feet for long durations causes itchiness and an unpleasant smell. Skin-friendly reusable sweat pads could be used to absorb sweat. Transportation of moisture and functionality is the current challenge that many researchers are working on. This study aims to develop a functional and breathable sweat pad with antimicrobial and quick drying performance. Three layered functional sweat pads (FSP) are prepared in which the inner layer is made of an optimized needle-punched coolmax/polypropylene nonwoven blend. This layer is then dipped in antimicrobial ZnO solution (2, 4, and 6 wt.%), and super absorbent polymer (SAP) is embedded, and this is called a functional nonwoven (FNW1) sheet. Electrospun nanofiber-based nanomembranes of polyamide-6 are optimized for bead-free fibers. They are used as a middle layer to enhance the pad’s functionality, and the third layer is again made of needle-punched optimized coolmax/polypropylene nonwoven sheets. A simple nonwoven-based sweat pad (SSP) is also prepared for comparison purposes. Nonwoven sheets are optimized based on better comfort properties, including air/water vapor permeability and moisture management (MMT). Nonwoven webs having a higher proportion of coolmax show better air permeability and moisture transfer from the inner to the outer layer. Antimicrobial activity of the functional nonwoven layer showed 8 mm of bacterial growth, but SSP and FSP showed only 6 mm of growth against Staphylococcus aureus. FSP showed superior comfort and antibacterial properties. This study could be a footstone toward highly functional sweat pads with remarkable comfort properties