Computer Internet Research Articles

IEEE Internet Computing: Special Issue on Knowledge-Infused Learning

IEEE Internet Computing: Special Issue on Knowledge-Infused Learning

Collaborative Edge Computing for Social Internet of Vehicles to Alleviate Traffic Congestion

Edge computing in vehicles is emerging as an essential candidate for the Internet of Vehicles (IoV) to improve traffic efficiency. The proliferation of IoV pushes the horizon of edge computing. The social features and connections among vehicles are significant for traffic efficiency solutions. However, it is quite challenging to perform collaborative edge computing (CEC) for social IoV systems because of network heterogeneity, vehicle mobility, user selfishness, privacy, and so on. This article focuses on the CEC, in the social IoV system to alleviate urban traffic congestion. Recent research reveals that intelligent traffic lights control through city-wide mobile edge computing (MEC) servers can reduce vehicles’ average waiting time at signal intersections. This article has focused on a CEC-based traffic management system (CEC-TMS) to reduce the average waiting time. It utilizes multiagent-based deep reinforcement learning (DRL) for the MEC servers that interact with IoV and traffic lights to generate dynamic green waves at congested intersections. Results demonstrate the effectiveness of the proposed system under the paradigm of multiagent DRL.

Anomaly detection‐based intelligent computing in internet of things and network applications

Anomaly detection‐based intelligent computing in internet of things and network applications

Preface

Preface

IEEE Internet Computing: Special Issue on Knowledge-Infused Learning

IEEE Internet Computing: Special Issue on Knowledge-Infused Learning

System analysis of digital economy virtualization processes

The virtualization of socio-economic processes is expressed in the development of various types of economic activities in the Internet computer network, acting as the infrastructure of the modern economic system, a catalyst for globalization processes, and the main means of communication between computers, information systems of various purposes and complexity, and people. The study of the theoretical and methodological problem of digital economy virtualization processes is due to the importance of determining the structure of virtualization as a set of interconnected industries, consumption, markets, and finance on the Internet. The elements of the system combine the types of economic activities, which include entrepreneurship on the Internet, as well as information and intellectual activities. The study of this problem was carried out using empirical methods of cognition of the structure of the system analysis of digital economy virtualization processes, along with the use of scientometric methods for reviewing the methodology of the educational process for training digital economy personnel and improving their qualifications as a precursor to the design of production processes, consumption, market and financial processes occurring in a digital environment. The conducted studies make it possible to obtain scientific results in the field of structuring the socio-economic processes of virtualization, namely: a dichotomy of virtualization processes in the digital economy is proposed, taking into account the factor of education; the positive and negative consequences of virtualization for the economy and society as a whole are identified. It was concluded in the course of the study that the system analysis of digital economy virtualization processes should be based on the development of the educational component and reflect the environment of virtualization processes, including digital platforms, which, first, form the global infrastructure of the world economy; second, they contribute to the development of entrepreneurship; third, they provide production, consumer, market and financial functions and corporate governance; fourth, they are a source of network externalities that create new social and economic problems. The prospect for further research is the development of a model for assessing the impact of the structure of virtualization processes on economic growth in the digital economy.

IEEE Internet Computing: Special Issue on the Effects of Social Media on Real-World Events

IEEE Internet Computing: Special Issue on the Effects of Social Media on Real-World Events

Secure Data Access Control with Cipher Text Update and Computation Outsourcing in Fog Computing for Internet of Things

Fog Computing is a region of Computer Science that is under steady construction and development, and related to data security, the worldview turns out to be more solid and secure for IoT's edge stages. The verification of limited memory devices has serious issues since memory utilization is high when applied with different models that have the motivation behind shared confirmation. In this paper, we propose the Novel cipher text-based encryption model (NCEM) which has an information access control plot dependent on Ciphertext-Policy it give information privacy, fine-grained control, and mysterious validation in a multi-authority fog computing framework. The sign cryption and plan cryption overhead for the client is altogether diminished by redistributing the bothersome calculation tasks to fog hubs. The proposed conspire is demonstrated to be secure in the standard model and can give trait repudiation and public unquestionable status. The security analysis, asymptotic multifaceted nature examination, and implementation results demonstrate that our construction can offset the security objectives with useful effectiveness in calculation.

Editorial: Special Section on Pervasive Edge Computing for Industrial Internet of Things

The papers in this special section focus on pervasive edge computing (PEC)for industrial Internet of Things. With the development of 5G technology and intelligent terminals, computation, communication, and storage capacities of devices are largely improved. Based on that, pervasive edge computing (PEC) becomes possible, where data can be processed on the network edge with the assistant of those intelligent terminals enhanced by 5G technology except the management of any centralized servers, including clouds and remote servers. The papers in this section solicits original research and practical contributions which advance PEC in industrial IoTs (IIoTs), regarding the architecture, technologies, and applications.

Role of E-Commerce in Insurance Industry

E-commerce consists of buying and selling of products and services over electronic systems such as the internet and other computer networks. E-commerce is a commercial activity dealing directly with the trading of goods and services and with other related business activities, in which the electronic communication medium plays a central role. These activities include the communication of information, the management of payment, the negotiating and trading of financial instruments and the management of transport. The e-business can be used for three primary processes which help to enhance the business and they are; • The Production Process • Customer Centric Process • Employee Centric Process The production processes is the first which include procurement, ordering and replenishment of stocks; processing of payments; electronic links with suppliers; and production control processes, among others. The second is customer-focused processes, which include promotional and marketing efforts, selling over the Internet, processing of customers purchase orders and payments, and customer support, among others. An internal management process The third includes employee services, training, internal information-sharing, video-conferencing, and recruiting. Generally electronic applications enhance information flow between production and sales forces to improve sales force productivity. The purpose of this paper is to find the benefits, challenges and success of e-commerce with special reference to Life Insurance Corporation of India.

Special Issue on AI-Powered 5G Services

This special issue of Internet Computing includes articles that tackle both the technical challenges and vast opportunities of AI-Powered 5G services. The first two papers deal with the use of AI and Machine Learning for improved resource utilization in 5G cellular networks, and provisioning in the 5G Core, respectively. The third paper presents a cautionary perspective by examining AI/ML for 5G and beyond through an adversarial lens, and finally, the last paper covers the study of a scalable 5G-based solution for real-time air quality monitoring that has the potential to improve the lives of millions impacted by air quality issues.

Parallel Computing for Efficient and Intelligent Industrial Internet of Health Things: An Overview

Internet of Things (IoT) is expanding and evolves into all aspects of the society. Research and developments in the field of IoT have shown the possibility of producing huge volume of data and computation among different devices of the IoT. The data collected from IoT devices are transferred to a central server which can further be retrieved and accessed by the service providers for analyzing, processing, and using. Industrial Internet of Health Things (IIoHT) is the expansion of the Internet of Health Things (IoHT) which plays an important role in observing, consulting, monitoring, and treatment process of remote exchange data processes. The linkage of computation and interoperability are supported through various intelligent sensors, controllers, and actuators. The role of parallel computing for efficient and Intelligent Industrial Internet of Health Things is obvious to analyze and process different healthcare situations. A detailed overview of this existing literature is needed through which the research community will provide new solutions for efficient healthcare with the help of IoT based on parallel computing. Therefore, the current study presents a detailed overview of the existing literature for facilitating IIoHT.

Multistrategy Repeated Game‐Based Mobile Crowdsourcing Incentive Mechanism for Mobile Edge Computing in Internet of Things

With the advent of the Internet of Things (IoT) era, various application requirements have put forward higher requirements for data transmission bandwidth and real‐time data processing. Mobile edge computing (MEC) can greatly alleviate the pressure on network bandwidth and improve the response speed by effectively using the device resources of mobile edge. Research on mobile crowdsourcing in edge computing has become a hot spot. Hence, we studied resource utilization issues between edge mobile devices, namely, crowdsourcing scenarios in mobile edge computing. We aimed to design an incentive mechanism to ensure the long‐term participation of users and high quality of tasks. This paper designs a long‐term incentive mechanism based on game theory. The long‐term incentive mechanism is to encourage participants to provide long‐term and continuous quality data for mobile crowdsourcing systems. The multistrategy repeated game‐based incentive mechanism (MSRG incentive mechanism) is proposed to guide participants to provide long‐term participation and high‐quality data. The proposed mechanism regards the interaction between the worker and the requester as a repeated game and obtains a long‐term incentive based on the historical information and discount factor. In addition, the evolutionary game theory and the Wright‐Fisher model in biology are used to analyze the evolution of participants’ strategies. The optimal discount factor is found within the range of discount factors based on repeated games. Finally, simulation experiments verify the existing crowdsourcing dilemma and the effectiveness of the incentive mechanism. The results show that the proposed MSRG incentive mechanism has a long‐term incentive effect for participants in mobile crowdsourcing systems.

A Novel Anonymous Authentication Scheme Based on Edge Computing in Internet of Vehicles

The vehicular cloud computing is an emerging technology that changes vehicle communication and underlying traffic management applications. However, cloud computing has disadvantages such as high delay, low privacy and high communication cost, which can not meet the needs of real-time interactive information of Internet of vehicles. Ensuring security and privacy in Internet of Vehicles is also regarded as one of its most important challenges. Therefore, in order to ensure the user information security and improve the real-time of vehicle information interaction, this paper proposes an anonymous authentication scheme based on edge computing. In this scheme, the concept of edge computing is introduced into the Internet of vehicles, which makes full use of the redundant computing power and storage capacity of idle edge equipment. The edge vehicle nodes are determined by simple algorithm of defining distance and resources, and the improved RSA encryption algorithm is used to encrypt the user information. The improved RSA algorithm encrypts the user information by reencrypting the encryption parameters . Compared with the traditional RSA algorithm, it can resist more attacks, so it is used to ensure the security of user information. It can not only protect the privacy of vehicles, but also avoid anonymous abuse. Simulation results show that the proposed scheme has lower computational complexity and communication overhead than the traditional anonymous scheme.

Digital financial inclusion risk prevention based on machine learning and neural network algorithms

In recent years, China has increased its investment in science and technology, and digital technologies such as mobile Internet, big data, and cloud computing have continuously made breakthroughs. The integration with the modern financial industry has stimulated online lending, third-party payment, digital insurance, and New financial forms such as digital wealth management are booming. With the rapid development of digital financial inclusion, the development of traditional financial industry has broken through time and geographical constraints, allowing more groups excluded from the traditional financial system to participate in financial activities and enjoy more convenient and faster personalized financial products and services, meet their financial needs and improve the reach of financial services. While the development of digital financial inclusion has benefited more groups, it has not changed the original risks of the financial industry. It has also brought about some negative external effects of financial technology, which poses greater challenges to the protection of financial consumers’ rights and interests. Therefore, this research aims at the digital inclusive risk prediction of financial institutions and personal risk prediction respectively, and proposes a financial risk prediction method based on the adaptive fusion of multi-source heterogeneous data, which can improve the effect of financial risk prediction through the effective use of multi-source data. purpose.

Digitalisation of the Economy of Social and Labour Relations in Modern Conditions

The authors represent data on the state of the process of digitalisation of the Russian economy and draw a conclusion about the high level of the information infrastructure development along with that they note a great gap in the digitalisation level between regions. When assessing the impact of the development of Internet technologies on employment, two main consequences have been identified: the reduction of the impact of the geographical factor on the supply and demand in the labour market and the involvement of previously unoccupied social groups in the production process. The rapid development of the digital economy, the accelerated industrialisation of digital technologies such as the Internet, big data and cloud computing, have led to further improvements in computing power, a significant reduction in computing costs, and a significant leap in data analysis and processing capabilities. The purpose of the study is to analyse and evaluate the effects of economy digitalisation on employment. Within the framework of the research conducted, both general scientific and specific scientific methods were used: formal and logical research methods (the method of induction, deduction, analogy, synthesis, comparison, observation, description, systematisation), formal and legal, historical and legal, comparative and legal, institutional, system analysis. The paper analyses the current global economic and technological trends that affect the transformation and formation of new socioeconomic relations in the context of the digital economy formation. This article examines the impact of the development of digital information technologies on the labour market and employment. The authors represent data on the state of the process of digitalisation of the Russian economy and draw a conclusion about the high level of the information infrastructure development along with that they note a great gap in the digitalisation level between regions. The results of the study can be used in the work of public authorities at all levels to develop and adjust programmes for the further labour market development and to prevent unemployment.

Computer Network Information Security Protection Faced by Digital Art Museums Based on the Internet of Things

The development of the Internet of things provides a great opportunity for the development of all walks of life, but it also brings many risks in the process, of which the most important thing is the protection of computer network information security. Digital art museums play a great role in viewing, education, and other functions. This article is aimed at analyzing the computer network information security protection problems faced by digital art museums. Analyze the application of the digital art gallery in the computer Internet of things, and combine the different aspects involved in the two parts to carry out experimental analysis and comparison. The difference between the various subjects of the digital art gallery, such as exhibits, writers, and visitors, is to maintain the security of Internet computer information. Introduce the application. The results show that compared with that of fog computing technology and that of edge computing technology, the performance of the Internet of things is generally better, with faster data processing speed, shorter processing time, higher quality, and stronger scalability. But at the same time, it is also facing greater computer network security threats. According to statistics, 83.3% of consumers worry about its usability but people are more concerned about its safety performance. Nearly 87.5% of consumers worry about whether their information will be leaked. When cloud computing technology is applied to digital art museums, how to protect computer network information security is particularly important. Based on the traditional firewall, this paper designs a hybrid firewall, which can better solve the problem of computer network information security.

Feature Selection with IG-R for Improving Performance of Intrusion Detection System

As the popularity of the internet computer continued to grow and become an indispensable in human life, the security of computer network has become an important issue in computer security field. The Intrusion Detection System (IDS) is a system used in computer security for network security. The feature selection stage of IDS is considered to be the most critical stage in IDS. This stage is very costly both in efforts and time. However, many machine learning approaches have been presented to improve this stage in order to improve the performance of an IDS. However, these approaches did not give desirable results with respect to the detection accuracy in the IDS. A novel technique is proposed in this paper combining the Information Gain and Ranker (IG+R) method as the feature selection strategy with Naive Bayes (NB), Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) as the classifiers. The performance of these IG+R-NB, IG+R-SVM, and IG+R-KNN was evaluated on NSLKDD dataset. The experimental results of our proposed method gave high accuracy and low false alarm rate. The results obtained was compared and benchmarked with existing works. The results of this paper outperformed the existing approaches in terms of the detection accuracy.

A Lightweight Internet Sharing Scheme for Sectional Medical Images according to Existing Hospital Network Facilities and Basic Information Security Rules.

Background With the outbreak of COVID-19, large-scale telemedicine applications can play an important role in the epidemic areas or less developed areas. However, the transmission of hundreds of megabytes of Sectional Medical Images (SMIs) from hospital's Intranet to the Internet has the problems of efficiency, cost, and security. This article proposes a novel lightweight sharing scheme for permitting Internet users to quickly and safely access the SMIs from a hospital using an Internet computer anywhere but without relying on a virtual private network or another complex deployment. Methods A four-level endpoint network penetration scheme based on the existing hospital network facilities and information security rules was proposed to realize the secure and lightweight sharing of SMIs over the Internet. A “Master-Slave” interaction to the interactive characteristics of multiplanar reconstruction and maximum/minimum/average intensity projection was designed to enhance the user experience. Finally, a prototype system was established. Results When accessing SMIs with a data size ranging from 251.6 to 307.04 MB with 200 kBps client bandwidth (extreme test), the network response time to each interactive request remained at approximately 1 s, the original SMIs were kept in the hospital, and the deployment did not require a complex process; the imaging quality and interactive experience were recognized by radiologists. Conclusions This solution could serve Internet medicine at a low cost and may promote the diversified development of mobile medical technology. Under the current COVID-19 epidemic situation, we expect that it could play a low-cost and high-efficiency role in remote emergency support.

Reputation Based Attacker Identification Policy for Multi-Access Edge Computing in Internet of Things

In the recent years, there has been an explosive growth of smart devices applications with high computational demands and critical latency. The Internet of Things (IoT) multi-access edge computing (MEC) framework offers a lower latency and a higher speed to the users, by offloading the cloud computing capabilities at the nearest edge of the mobile network. In this operating scenario, the proper allocation of limited resources is one of the biggest challenges, and security is becoming vital as the number of devices in an IoT network tends to billions. According to recent studies, even authorized edge devices may be a significant threat for IoT networks (i.e., selfish behavior), as a result of mixed service structures with a wide range of different requirements. Thus, this work proposes a novel two-fold method to allocate resources and then identify attackers (selfish IoT malicious devices) by means of a reputation-based stable matching policy. The devices are categorized in three different states, namely honest, suspicious, and malicious states, according to their reputation indices. Our algorithm allows to move the devices between the three states, in order to exclude malicious devices and to rehabilitate users identified as unintentional attackers (due to bad propagation conditions). Theoretical and simulation results confirm the validity and effectiveness of such approach for identifying malicious IoT devices in MEC networks.