Configuration Method of AWS Security Architecture That Is Applicable to the Cloud Lifecycle for Sustainable Social Network

Recently, due to the many features and advantages of cloud computing, “cloud service” is being introduced to countless industries around the world at an unbelievably rapid pace. However, with the rapid increase in the introduction of cloud computing services, security vulnerabilities are increasing and the risk of technology leakage from cloud computing services is also expected to increase in social network service. Therefore, this study will propose an AWS-based (Amazon Web Services) security architecture configuration method that can be applied for the entire life cycle (planning, establishment, and operation) of cloud services for better security in AWS Cloud Services, which is the most used cloud service in the world. The proposed AWS security guide consists of five different areas, Security Solution Selection Guide, Personal Information Safeguard Guide, Security Architecture Design Guide, Security Configuration Guide, and Operational Security Checklist, for a safe social network. The AWS Security Architecture has been designed with three reference models: Standard Security Architecture, Basic Security Architecture, and Essential Security Architecture. The AWS Security Guide and AWS Security Architecture proposed in this paper are expected to help many businesses and institutions that are hoping to establish and operate a safe and reliable AWS cloud system in the social network environment.

Comparing Deep Neural Networks and Gradient Boosting for Pneumonia Detection Using Chest X-Rays

In recent years, with the development of computational power and the explosion of data available for analysis, deep neural networks, particularly convolutional neural networks, have emerged as one of the default models for image classification, outperforming most of the classical machine learning models in this task. On the other hand, gradient boosting, a classical model, has been widely used for tabular structure data and leading data competitions, such as those from Kaggle. In this study, the authors compare the performance of deep neural networks with gradient boosting models for detecting pneumonia using chest x-rays. The authors implement several popular architectures of deep neural networks, such as Resnet50, InceptionV3, Xception, and MobileNetV3, and variants of a gradient boosting model. The authors then evaluate these two classes of models in terms of prediction accuracy. The computation in this study is done using cloud computing services offered by Google Colab Pro.

A Proposed Architecture f or Placement of Cloud Data Centre in Software Defined Network Environment

Emerging technologies like IoT (Internet of Things) and wearable devices like Smart Glass, Smart watch, Smart Bracelet and Smart Plaster produce delay sensitive traffic. Cloud computing services are emerging as supportive technologies by providing resources. Most services like IoT require minimum delay which is still an area of research. This paper is an effort towards the minimization of delay in delivering cloud traffic, by geographically localizing the cloud traffic through establishment of Cloud mini data centers. The anticipated architecture suggests a software defined network supported mini data centers connected together. The paper also suggests the use of segment routing for stitching the transport paths between data centers through Software defined Network Controllers.

A Cluster Analysis Concerning the Behavior of Enterprises with E-Commerce Activity in the Context of the COVID-19 Pandemic

The planning of activities of e-commerce enterprises and their behavior has been influenced by the emergence of the COVID-19 pandemic. The behavior of e-commerce enterprises has been highlighted at the level of EU countries through an analysis elaborated on four variables: the value of e-commerce sales, cloud computing services, enterprises that have provided training to develop/upgrade the ICT skills of their personnel, e-commerce, customer relationship management (CRM) and secure transactions. Using the hierarchical clustering method, analysis was carried out on these variables to identify certain economic and behavioral patterns of e-commerce activity from 2018 and 2020. The study of the relationships involved in the e-commerce activity of these enterprises is reflected in models of the economic behavior of 31 European states in relation to the targeted variables. The results show that the impacts of the COVID-19 pandemic are strongly manifested in the direction of the evolution of each indicator but differ from one country to another. The trends depend on the level of development and the particularities of each country’s economy in adapting to the repercussions reported in relation to the level of impact of the COVID-19 pandemic. This is highlighted by the significant regrouping of countries in 2020 compared with 2018 in relation to the average values of the indicators. The results show that, in 2020, the most significant percentages of the value of e-commerce sales were recorded in Belgium, Ireland and Czechia, as in 2018. In e-commerce, customer relationship management and secure transactions, Denmark and Sweden were superior in 2020 to the countries mentioned above, which were dominant in 2018. For the other two indicators, Finland and Norway were the top countries included in the analysis in both years. The conclusion supports the continuous model of e-commerce enterprise behavior in order to meet the requirements of online customers.

Information and communication technologies for intelligent control of ground unmanned multipur-pose vehicles

At present, there is a situation when the practice of creating modern devices, units and systems of ground unmanned vehicles (GUV) has preceded the theory of information analysis and synthesis of complex systems. Some existing solutions for the information support of the GUV need to be generalized, standardized and unified, the definition of new special requirements for the creation of computer systems and networks in transport should be made. Therefore, it is necessary and actual to develop information and communication technology for intelligent control of multi-purpose GUV. Goal. The purpose of the article is to develop information and communication technology for intelligent control of multi-purpose GUV, which work in conditions of intensive loads, difficult operating conditions, increased responsibility of mechanisms, resulting in reduced human losses and energy consumption, increased machine reliability and control accuracy. Methodology. The methodology of tasks is based on the use of a synergetic approach to the creation of information and communication technology for intelligent control of multi-purpose GUV, as the development of a systematic approach taking into account the adaptation and integration of the vehicle to transport infrastructure and/or rough terrain. The principles of synergetics underlie the construction of mechatronic systems – a combination in one unit of components of different technical nature (mechanical, electrical, computer), which adaptively interact with the external environment as a single functional and structural organism. The synergetic approach deals with phenomena and processes, as a result of which the system – as a whole – may have properties that none of the parts has. Results. The concept of intelligent control of multi-purpose GUV on the basis of artificial hybrid neuro-phase regulators with the use of cloud computing services and deep learning technology is proposed, substantiated and implemented, which allows to qualitatively increase the efficiency of both one vehicle and the transport system on the base combining a synergetic approach and evolutionary methods of learning multilayer artificial neural networks by objectively forming the architecture of these networks on the basis of learning functionalities and appropriate control objectives. Originality. Use of cloud computing services based on deep learning for intelligent control technology of GUV. Practical value. The proposed information and communication technology of intelligent control of multi-purpose GUV will significantly reduce energy consumption, psychophysical stress on crew members, as well as increase the accuracy of location.

Government Cloud Procurement

In Government Cloud Procurement, Kevin McGillivray explores the question of whether governments can adopt cloud computing services and still meet their legal requirements and other obligations to citizens. The book focuses on the interplay between the technical properties of cloud computing services and the complex legal requirements applicable to cloud adoption and use. The legal issues evaluated include data privacy law (GDPR and the US regime), jurisdictional issues, contracts, and transnational private law approaches to addressing legal requirements. McGillivray also addresses the unique position of governments when they outsource core aspects of their information and communications technology to cloud service providers. His analysis is supported by extensive research examining actual cloud contracts obtained through Freedom of Information Act requests. With the demand for cloud computing on the rise, this study fills a gap in legal literature and offers guidance to organizations considering cloud computing.

Data Confidentiality in Cloud Storage. A Survey

In cloud computing security, privacy and data confidentiality plays important role when popularity in terms of cloud computing services is consider. Till now there are various schemes, protocols and architecture for cloud computing privacy and data protection are proposed which are based on data confidentiality, cryptographic solution, cipher text blocks, various transforms, symmetric encryption schemes, attribute-based encryption, trust and reputation, access control, etc., but they are scattered and lacking uniformity without proper security logic. This paper systematically reviews as well as analyze research done in this relevant area. First various shortcomings in cloud computing, architectures, framework and schemes proposed for data confidentiality will be discussed; then existing cryptographic schemes, encryption functions, linear transform, grid storage system, key exposure, secret sharing, AONT (All or Nothing Transform), dispersed storage, trust, block encryption mechanism, attribute-based encryption, access control will be discussed; thirdly propose future direction with research challenges for data confidentiality in cloud computing; finally focus is on concern data confidentiality scheme to overcome the technical deficiency and existing schemes.