Hybrid Computational Modeling for Web Application Security Assessment

Transformation from conventional business management systems to smart digital systems is a recurrent trend in the current era. This has led to digital revolution, and in this context, the hardwired technologies in the software industry play a significant role However, from the beginning, software security remains a serious issue for all levels of stakeholders. Software vulnerabilities lead to intrusions that cause data breaches and result in disclosure of sensitive data, compromising the organizations’ reputation that translates into, financial losses as well. Most of the data breaches are financially motivated, especially in the healthcare sector. The cyber invaders continuously penetrate the E-Health data because of the high cost of the data on the dark web. Therefore, security assessment of healthcare web-based applications demands immediate intervention mechanisms to weed out the threats of cyber-attacks. The aim of this work is to provide efficient and effective healthcare web application security assessment. The study has worked with the hybrid computational model of Multi-Criteria Decision Making (MCDM) based on Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal-Solutions (TOPSIS) under the Hesitant Fuzzy (HF) environment. Hesitant fuzzy sets provide effective solutions to address decision making problems where experts counter hesitation to make a decision. The proposed research endeavor will support designers and developers in identifying, selecting and prioritizing the best security attributes for web applications’ development. The empirical analysis concludes that Robustness got highest priority amongst the assessed security attributes set followed by Encryption, Authentication, Limit Access, Revoke Access, Data Validation, and Maintain Audit Trail. The results of this research endeavor depict that this proposed computational procedure would be the most conversant mechanism for determining the web application security. The study also establishes guidelines which the developers can refer for the identification and prioritization of security attributes to build more secure and trustworthy web-based applications.     

Quantum Remote State Preparation Based on Quantum Network Coding

As an innovative theory and technology, quantum network coding has become the research hotspot in quantum network communications. In this paper, a quantum remote state preparation scheme based on quantum network coding is proposed. Comparing with the general quantum remote state preparation schemes, our proposed scheme brings an arbitrary unknown quantum state finally prepared remotely through the quantum network, by designing the appropriate encoding and decoding steps for quantum network coding. What is worth mentioning, from the network model, this scheme is built on the quantum k-pair network which is the expansion of the typical bottleneck network—butterfly network. Accordingly, it can be treated as an efficient quantum network preparation scheme due to the characteristics of network coding, and it also makes the proposed scheme more applicable to the large-scale quantum networks. In addition, the fact of an arbitrary unknown quantum state remotely prepared means that the senders do not need to know the desired quantum state. Thus, the security of the proposed scheme is higher. Moreover, this scheme can always achieve the success probability of 1 and 1-max flow of value k. Thus, the communication efficiency of the proposed scheme is higher. Therefore, the proposed scheme turns out to be practicable, secure and efficient, which helps to effectively enrich the theory of quantum remote state preparation.     

Hyperparameter Tuned Deep Learning Enabled Cyberbullying Classification in Social Media

Cyberbullying (CB) is a challenging issue in social media and it becomes important to effectively identify the occurrence of CB. The recently developed deep learning (DL) models pave the way to design CB classifier models with maximum performance. At the same time, optimal hyperparameter tuning process plays a vital role to enhance overall results. This study introduces a Teacher Learning Genetic Optimization with Deep Learning Enabled Cyberbullying Classification (TLGODL-CBC) model in Social Media. The proposed TLGODL-CBC model intends to identify the existence and non-existence of CB in social media context. Initially, the input data is cleaned and pre-processed to make it compatible for further processing. Followed by, independent recurrent autoencoder (IRAE) model is utilized for the recognition and classification of CBs. Finally, the TLGO algorithm is used to optimally adjust the parameters related to the IRAE model and shows the novelty of the work. To assuring the improved outcomes of the TLGODL-CBC approach, a wide range of simulations are executed and the outcomes are investigated under several aspects. The simulation outcomes make sure the improvements of the TLGODL-CBC model over recent approaches.     

Homogeneous and polymorphic transformations to ordered intermetallics in nanostructured Au–Cu multilayer thin films

Journal of Materials Science - Atomic arrangements in the nanostructured grains and interfaces of thermally evaporated Au/Cu multilayer thin films on polycrystalline Si substrate have been explored...     

Introduction,production, characterization and applications of defects in graphene

Journal of Materials Science: Materials in Electronics - The successful preparation of graphene in research laboratory has brought a revolutionary progress in almost all the research fields...     

Solution‐Processed Ti3C2Tx MXene Antennas for Radio‐Frequency Communication

Highly integrated, flexible, and ultrathin wireless communication components are in significant demand due to the explosive growth of portable and wearable electronic devices in the fifth‐generation (5G) network era, but only conventional metals meet the requirements for emerging radio‐frequency (RF) devices so far. Here, it is reported on Ti₃C₂T_x MXene microstrip transmission lines with low‐energy attenuation and patch antennas with high‐power radiation at frequencies from 5.6 to 16.4 GHz. The radiation efficiency of a 5.5 µm thick MXene patch antenna manufactured by spray‐coating from aqueous solution reaches 99% at 16.4 GHz, which is about the same as that of a standard 35 µm thick copper patch antenna at about 15% of its thickness and 7% of the copper weight. MXene outperforms all other materials evaluated for patch antennas to date. Moreover, it is demonstrated that an MXene patch antenna array with integrated feeding circuits on a conformal surface has comparable performance with that of a copper antenna array at 28 GHz, which is a target frequency in practical 5G applications. The versatility of MXene antennas in wide frequency ranges coupled with the flexibility, scalability, and ease of solution processing makes MXene promising for integrated RF components in various flexible electronic devices.     

MXenes Antibacterial Properties and Applications: A Review and Perspective

The mutations of bacteria due to the excessive use of antibiotics, and generation of antibiotic-resistant bacteria have made the development of new antibacterial compounds a necessity. MXenes have emerged as biocompatible transition metal carbide structures with extensive biomedical applications. This is related to the MXenes’ unique combination of properties, including multifarious elemental compositions, 2D-layered structure, large surface area, abundant surface terminations, and excellent photothermal and photoelectronic properties. The focus of this review is the antibacterial application of MXenes, which has attracted the attention of researchers since 2016. A quick overview of the synthesis strategies of MXenes is provided and then summarizes the effect of various factors (including structural properties, optical properties, surface charges, flake size, and dispersibility) on the biocidal activity of MXenes. The main mechanisms for deactivating bacteria by MXenes are discussed in detail including rupturing of the bacterial membrane by sharp edges of MXenes nanoflakes, generating the reactive oxygen species (ROS), and photothermal deactivating of bacteria. Hybridization of MXenes with other organic and inorganic materials can result in materials with improved biocidal activities for different applications such as wound dressings and water purification. Finally, the challenges and perspectives of MXene nanomaterials as biocidal agents are presented.     

Hydrothermal synthesis of ZnO/C microflowers for photocatalytic degradation of organic pollutants under visible light irradiation: kinetics,mechanism and recyclability

Journal of Materials Science: Materials in Electronics - We developed an improved hexagonal wurtzite ZnO and ZnO/C microflowers through the facile hydrothermal technique. The obtained...     

Photocatalytic activity and radiation-attenuation ability of copper ions surface-doped dysprosium oxide

Journal of Materials Science: Materials in Electronics - Herein, Cu ions surface-doped Dy2O3 photocatalyst (Cu–Dy2O3) is synthesized utilizing hydrothermal technique to degrade methyl violet...     

Novel NiO/ZnO/Fe2O3 white light-emitting phosphor: facile synthesis,color-tunable photoluminescence and robust photocatalytic activity

Journal of Materials Science: Materials in Electronics - The NiO/ZnO/Fe2O3 ternary nanocomposites with different molar ratios (1:1:1), (2:1:1), (3:1:1) and (4:1:1) were synthesized by...