Mobile Social Networking

The increasing popularity and improvement of social media have brought us a lot of benefits, including a convenience relationship and a more responsive mass media. But along with this metamorphosis there has been a proliferation of cyber security threats that have increased both in size and complexity. From phishing and malware to identity theft and disinformation, social media sites such as Facebook, Instagram, Twitter and TikTok are perfect platforms for a range of cyber threats. AI Cyber criminals have already started using various AI (artificial intelligence) tools to launch targeted attacks, which include AI-powered phishing, deep fakes and social engineering. This everchanging nature of threats has made the role of defense-and-, in an offensive stance, offense-systems more and more critical. This paper examines the forms of cyber threats that are emerging in social media, as well as the new risks that AI and other digital technologies have contributed, and existing means to mitigate cyber risks. It highlights the need for user awareness, multi-factor authentication, and monitoring of accounts for individuals as well as organizations. Moreover, it emphasizes the need for developing integrated, proactive defenses to address the challenge of growing cyber threats in an increasingly social world. Through real-life examples and a look at advances in threat detection, this paper identifies practical ways to address the increasing cyber risk resulting from social media use and achieve safer online interactions.

The use of social media is spreading and today, there are various social media platforms such as blogs, microblogs, social networking sites, and collaborative projects. While its use and adoption is well-studied, the same cannot be said for the non-use and abandonment of social media. This study examines the reasons for the non-use and abandonment of two social media platforms, namely Facebook and Twitter. A survey questionnaire was developed and distributed to non-users and abandoners of Twitter/Facebook. The findings indicate that Facebook is preferred over Twitter while our analysis has found that the reasons for the non-use and abandonment of both platforms are similar, with privacy concerns being one of the main reasons.

In a power distribution system of most of the buildings, A Low Voltage (L.V.) switchboard was applied to protect the system. There are different components in the switchboard (e.g. circuit breakers, over current protection relay, earth fault protection relay etc.). There are also some components for measure the power quality which is the power analyser. A power analyser (including Voltmeter, Ammeter, Multi-meter) is using to measure the power quality in the electrical power distribution system. Most of the electrical power distributions systems have been connected the power analysers to a building management system. The power analysers connected to a computer in a fixed position that means if someone wants to check the power distribution status, the person needs to go to the computer to check. In this project, a system would be made to monitoring the power status by 5G New Radio (NR) Network application with android smartphone. Since 5G NR Network can provide a theoretical peak download capacity of 20 Gigabits per second. It would be more convenient to monitoring the power status in different place by checking though in the Internet of Things (IoT) .

In a power distribution system of most of the buildings, A Low Voltage (L.V.) switchboard was applied to protect the system. There are different components in the switchboard (e.g. circuit breakers, over current protection relay, earth fault protection relay etc.). There are also some components for measure the power quality which is the power analyser. A power analyser (including Voltmeter, Ammeter, Multi-meter) is using to measure the power quality in the electrical power distribution system. Most of the electrical power distributions systems have been connected the power analysers to a building management system. The power analysers connected to a computer in a fixed position that means if someone wants to check the power distribution status, the person needs to go to the computer to check. In this project, a system would be made to monitoring the power status by 5G New Radio (NR) Network application with android smartphone. Since 5G NR Network can provide a theoretical peak download capacity of 20 Gigabits per second. It would be more convenient to monitoring the power status in different place by checking though in the Internet of Things (IoT) .

Mining software repositories (MSR) research had significantly contributed to software engineering. However, MSR results integration across repositories is a recent concern that is getting more attention from researchers each day. Some noticeable research in this sense is related to the approximation between MSR and semantic web, specially linked data approaches which makes it possible to integrate repositories and mined results. Manifested that way, we believe that current research is not fully addressing the practical integration of MSR results, specially, in software engineering due to not considering that these results needs to be integrated to the tools as assistance to activity performers, as a kind of decision making support. Based on this statement this research describes an approach, named Sambasore, which is concerned with MSR results inter-repository integration and also to decision making support processes, based on tool assistance modelling. To show its feasibility we describe the main concepts, some related works and also a proof of concept experiment applied to a software process modelling tool named Spider PM.

In the research of wireless communications, prototypes and measurements on real test-beds provide insights and fundamental information for a realistic tuning of simulation models. Recently there has been an increasing interest in exploring one of the critical fundamentals: the realistic radio range irregularity (RRI) model. This research builds on the IEEE 802.11, and investigates such a practical RRI model according to the measurements made under various settings. Using the RRI model, a set of representative localization algorithms are evaluated and compared. Through detailed analysis and extensive simulations, the paper points out how the localization performance is affected by the use of simplistic models. Moreover, some algorithms perfoming well under simplistic models do not work in real world settings. The RRI model reflects and highligths the weaknesses of those algorithms and allow the design of countermeasures. This paper introduces a constrained-greedy forwarding radio propagation method to remedy the negative effects encountered under actual operating environments.

Online messaging platforms such as WhatsApp, Telegram, and Discord, each with hundreds of millions of users, are one of the dominant modes of communicating or interacting with one another. Despite the widespread use of public group chats, there exists no systematic or detailed characterization of these group chats. There is, more importantly, lack of a general understanding of how these (public) groups dier in characteristics and use across the dierent platforms. We also do not know whether the messaging platforms expose personally identiable information, and we lack a comprehensive view of the privacy implications of leaks for the users. In this work, we address these gaps by analyzing the messaging platforms' ecosystem through the lens of a popular social media platform-Twitter. We search for WhatsApp, Telegram, and Discord group URLs posted on Twitter over a period of 38 days and amass a set of 351K unique group URLs. We analyze the content accompanied by group URLs on Twitter, nding interesting dierences related to the topics of the groups across the multiple messaging platforms. By monitoring the characteristics of these groups, every day for more than a month, and, furthermore, by joining a subset of 616 groups across the dierent messaging platforms, we share key insights into the discovery of these groups via Twitter and reveal how these groups change over time. Finally, we analyze whether messaging platforms expose personally identiable information. In this paper, we show that (a) Twitter is a rich source for discovering public groups in the dierent messaging platforms, (b) group URLs from messaging platforms are ephemeral, and (c) the considered messaging platforms expose personally identiable information, with such leaks being more prevalent on WhatsApp than on Telegram and Discord.

PurposeA great number of people use mobile social networks (MSNs) to communicate, entertain, learn, search and get advice. Growth and survival of any community depends on the activities of its members in sharing information and knowledge. The purpose of this study is to assess the influential factors on knowledge sharing behavior in MSNs in different perspectives in a comprehensive manner.Design/methodology/approachA model of factors affecting knowledge sharing behavior in MSNs is proposed by applying the structural equation modeling and path analysis to data collected from a sample of users of a well-known MSN through a questionnaire.FindingsThis study supports the contributive aspects of trust and enjoying participation in sharing knowledge, while there is no significant correlation between perceived ease of use and knowledge sharing behavior in MSNs. Furthermore, intention to share knowledge can lead to actual behavior in MSNs environments.Practical implicationsThe results obtain...

Social media websites are becoming more prevalent on the Internet. Sites, such as Twitter, Facebook, and Instagram, spend significantly more of their time on users online. People in social media share thoughts, views, and facts and create new acquaintances. Social media sites supply users with a great deal of useful information. This enormous quantity of social media information invites hackers to abuse data. These hackers establish fraudulent profiles for actual people and distribute useless material. The material on spam might include commercials and harmful URLs that disrupt natural users. This spam content is a massive problem in social networks. Spam identification is a vital procedure on social media networking platforms. In this paper, we have proposed a spam detection artificial intelligence technique for Twitter social networks. In this approach, we employed a vector support machine, a neural artificial network, and a random forest technique to build a model. The results in...

There has been tremendous growth in Global System for Mobile (GSM) services in Nigeria in the last two decade. The rapid development of GSM telecommunication industries have given rise to need for how the GSM services are delivered to customers efficiently. This paper is on GSM quality of service (QoS) performance in, Abuja Nigeria. The study investigates network transmission impairment and offers some useful remedies. The method involved use of Sony Ericson W-995 phone to gather data on physical network impairments in selected densely populated areas of Abuja. The data obtained were from four major GSM service providers MTN, Etisalat, Glo and Airtel. Assessment in terms of Key Performance Indicator (KPI) using Transmission Environment Monitory System (TEMS) Discovery professional software carried out on the networks under test. The results obtained from the analysis indicated that QoS performance of Airtel is slightly better than the other three GSM services providers tested within Nyanyan, Gwagwalada, and Wuse areas in Abuja. .

This Digital Forensics is fundamental for the fruitful indictment of computer criminals. Although there are several vital steps that got to be considered and taken for successful examination, Digital Forensics faces several challenges at a certain level wherein computerized evidence is developing and growing at a huge scale. There are high-paced advancements in computer science and information technology that enables inventive methods for digital investigations. This when machine learning, a branch of study from the field of artificial intelligence plays an important role in analyzing large amounts of data to reveal any criminal activity. It has an aim to learn the historical activities of the crime to predict and prevent these behaviors in the future. In this paper we will be delving into the application of machine learning algorithms in detecting frauds and where do frauds originate from. For this study, we have considered one of the root causes of fraudulent case i.e. Email Phishing and investigated its traditional methods to detect it. However, the approach can be rectified by implementing machine learning algorithms such as Random Forest and Support Vector Machine (SVM) and deploying a framework introduced here in the coming chapter which will give us the right results by using the performance metrics.

In this paper, we present the design and the implementation of a contextual and multimodal information diffusion system for museums. We propose a proactive service (1) with the ability to sense the profile of nearby visitors, using RFID and WLAN connectivity, (2) that adapts the information content to the target user, and finally (3) that distributes automatically the information to several devices, collective devices like large wall panels disseminated in museum or directly to digital guide carried by visitors.

This paper proposes a new technique to improve error performance for the min-sum decoding algorithm for the low density parity check code. The proposed technique is based on two way normalization of min-sum LDPC decoding algorithm. The variable message is modified by two normalization factors to achieve the optimum approximation for the magnitude overestimation at the check node processing. This new method does not need to search for the optimum normalization factor for min-sum algorithm when there is a change in code length and rate. The performance has been evaluated for medium and short length codes and for small number of iterations. The results show outperformance of this new proposed method which makes it suitable for many practical applications.

This paper tackles an RFID based location finding and tracking system. The system is an integral part of a navigation aid being developed for guiding visually disabled people in a store. The aid is composed of a portable hardware interface unit, a standalone RFID unit, and a central processing unit. The units interact via wireless communication to locate the position of the user in a known indoor environment and tracking his/her movement. An active RFID tag helps to estimate the location of a user and the user is guided to follow a route accordingly, via a tactile compass. The system uses RF signal strengths and is based on Bayes Decision Theory. Initial simulation results with the system prove promising for location finding and tracking, especially when the tracked person is guided by a system.

Video on Demand (VOD) system over the wireless mobile network is a system that provides video services to mobile clients. The main problem with these systems is the high service delay where the mobile clients have to wait to view their favorite movie. The importance of this paper is based on finding a solution on how to reduce the delay time in the VOD system. This paper introduces a novel caching mechanism named Proxy Server Cache mechanism to tackle the issue of service delay. This delay happens when the broadcasting phase that is related to the first segment is missed by a client from the current broadcasting channels. In this mechanism, the video's first segment is stored on a server of a stationary proxy type. The delayed clients will directly acquire the first segment from the proxy server instead of waiting for the following broadcasting channel pertaining to the first segment. The proposed scheme ensuresobtaining the first segment from mobile clients when they arrive. Additionally, the performance of the proposed scheme is validated by applying the VOD system, which can involve the balancing mechanism to retain particular requests through to the local proxy server to provide a fair dissemination for these requests. The obtained result confirms that the proposed scheme reduces the time delay of the system in comparison with the best existing schemes. The results of the average time delay in the Proxy-Cache scheme is 179.2505 milliseconds when 10 clients arrive each minute (Client/minute), the average time delay is 140 milliseconds when the video lengths are 30, 60 and 90. Meanwhile, the failure probability for obtaining the first segment of the video remains zero when the number of arrived requests is set to2, 4, 6, 8 and 10.

Vehicular Adhoc Networks (VANETs) are emerging as a crucial component in the development of Intelligent Transportation Systems (ITS). These networks aim to enhance traffic operations, increase safety, and facilitate communication between vehicles and infrastructure. However, VANETs face significant privacy and security challenges. This study proposes a novel approach to address VANET energy efficiency and privacy analysis using a trust-based authentication system and deep learning methods. Attention layer integrated gradient kernel vector flow neural networks are utilized for classifying monitored data to detect malicious users. The hybrid multipath energy-efficient routing protocol contributes to improved energy efficiency. The experimental analysis evaluates energy efficiency, latency, throughput, packet delivery ratio, computational cost, and communication overhead, and trust value analysis. The proposed technique achieved energy efficiency of 99%, latency of 63%, throughput of 9...

In this paper, we propose a Voronoi diagram based spatio-temporal data redundancy elimination approach for RFID systems having multiple readers so that every RFID tag will be read by only one reader depending on the distance between the tag and the center of the Minimum Enclosing Circle (MEC) of the Voronoi cell which the reader belongs to. Thus, the spatial redundancy in the gathered data is completely eliminated. Temporal redundancy is also minimized by reading the RFID tags at regular time intervals larger than an appropriately chosen threshold value. Existing methods of reducing data redundancy in RFID systems are often associated with loss of data, false positive errors and false negative errors. In contrast to this, our proposed technique is free from any false positive and false negative errors with no loss of data and every tag being read by only one single reader. Simulation of our proposed approach also establishes its superiority to the existing techniques in terms of the...

In the research of wireless communications, prototypes and measurements on real test-beds provide insights and fundamental information for a realistic tuning of simulation models. Recently there has been an increasing interest in exploring one of the critical fundamentals: the realistic radio range irregularity (RRI) model. This research builds on the IEEE 802.11, and investigates such a practical RRI model according to the measurements made under various settings. Using the RRI model, a set of representative localization algorithms are evaluated and compared. Through detailed analysis and extensive simulations, the paper points out how the localization performance is affected by the use of simplistic models. Moreover, some algorithms perfoming well under simplistic models do not work in real world settings. The RRI model reflects and highligths the weaknesses of those algorithms and allow the design of countermeasures. This paper introduces a constrained-greedy forwarding radio propagation method to remedy the negative effects encountered under actual operating environments.

Vehicular Ad-hoc network (VANET) is one of the emerging technologies for research community to get various research challenges to construct secured framework for autonomous vehicular communication. The prime concern of this technology is to provide efficient data communication among registered vehicle nodes. The several research ideas are implemented practically to improve overall communication in VANETs by considering security and privacy as major aspects of VANETs. Several mechanisms have been implemented using cryptography algorithms and methodologies. However, these mechanisms provide a solution only for some restricted environments and to limited security threats. Hence, the proposed novel mechanism has been introduced, implemented and tested using key management technique. It provides secured network environment for VANET and its components. Later, this mechanism provides security for data packets of emergency messages using cryptography mechanism. Hence, the proposed novel me...

It is common knowledge that the transition of mobile networks from one generation to another is basically for the improvement in the network’s Quality of Service (QoS). Bearing this in mind, we will assumme that the Universal Mobile Telecommunication System (UMTS) will outperform the Global System for Mobile Communication (GSM), hence, the motivation to conduct this study in Calabar, Nigeria, for four mobile networks; MTN, Airtel, Globacom and 9mobile. With the aid of a TEMS investigation software installed in a laptop, a measurement campaign was carried out and log files collected, with focus on Call Setup Success Rate (CSSR), Dropped Call Rate (DCR), Handover Success Rate (HOSR), Call Setup Time (CST), network coverage and network quality. The collected data was analyzed with the aid of a TEMS discovery software. The analyzed data for each Key Performance Indicator (KPI) was compared with the minimum benchmark of the telecommunications regulatory body, the Nigerian Communication C...

In the research of wireless communications, prototypes and measurements on real test-beds provide insights and fundamental information for a realistic tuning of simulation models. Recently there has been an increasing interest in exploring one of the critical fundamentals: the realistic radio range irregularity (RRI) model. This research builds on the IEEE 802.11, and investigates such a practical RRI model according to the measurements made under various settings. Using the RRI model, a set of representative localization algorithms are evaluated and compared. Through detailed analysis and extensive simulations, the paper points out how the localization performance is affected by the use of simplistic models. Moreover, some algorithms perfoming well under simplistic models do not work in real world settings. The RRI model reflects and highligths the weaknesses of those algorithms and allow the design of countermeasures. This paper introduces a constrained-greedy forwarding radio propagation method to remedy the negative effects encountered under actual operating environments.

Recently, the increasing demand to transfer data through the Internet has pushed the Internet infrastructure to the final edge of the ability of these networks. This high demand causes a deficiency of rapid response to emergencies and disasters to control or reduce the devastating effects of these disasters. As one of the main cornerstones to address the data traffic forwarding issue, the Internet networks need to impose the highest priority on the special networks: Security, Health, and Emergency (SHE) data traffic. These networks work in closed and private domains to serve a group of users for specific tasks. Our novel proposed network flow priority management based on ML and SDN fulfills high control to give the required flow priority to SHE data traffic. The proposal relies on selected header bits from the traffic class field of a packet using the ML to prioritize traffic flows according to the precedence levels by governing the Differentiated Services Code Point (DSCP) bits in keeping with network administrator policies. The proposed network has been evaluated and performed utilizing the MATLAB platform and the Mininet simulator. The results of extensive testing show enhancement by applying our forcing priority algorithm obtained an efficient reduction in queuing delay and lost packets. The average waiting time in queue was reduced by around 61%, and the lost packets hit 0.005% when adopting the SDN-based ML network traffic priority management. 15 INDEX TERMS AI, DSCP, packet header, precedence level, SDN. I. INTRODUCTION 16 Nowadays, the world is experiencing natural terrible changes 17 and challenges besides terrorist threats. In order to prevent 18 or at least reduce the destructive effects of these disasters, 19 world countries need reliable and trusted communication net-20 works. Such special networks will help in saving the people 21 and the country's national security. Therefore, these special 22 networks have the highest traffic priority to ensure speed 23 response by responsible humans. To enable the forward-24 ing of Security, Health, and Emergency (SHE)'s data traffic 25 over Internet networks, this data traffic must be deported 26 and transferred through public telecommunication networks. 27 The associate editor coordinating the review of this manuscript and approving it for publication was Qingli Li. This process requires that communication networks include diverse and modern technologies such as Machine Learning (ML), Artificial Intelligence (AI) [1], and Software-Defined Networking (SDN) to attain the highest performance of these networks [2]. To guarantee efficient data transferring of SHE networks across the public Internet links, that needs to dedicate the highest priority for this data if these special networks fail in the wake of severe risks. The term ''special networks'' in this paper indicates that networks connect their users within a private and authenticated login to communicate with each other in close domain networks. As examples of such networks are Ad hoc [3], security or police, cellular, and health networks. However, some of these networks are considered confidential, secretive, and not available for public use. Therefore, there is restricted

Recently, the increasing demand to transfer data through the Internet has pushed the Internet infrastructure to the final edge of the ability of these networks. This high demand causes a deficiency of rapid response to emergencies and disasters to control or reduce the devastating effects of these disasters. As one of the main cornerstones to address the data traffic forwarding issue, the Internet networks need to impose the highest priority on the special networks: Security, Health, and Emergency (SHE) data traffic. These networks work in closed and private domains to serve a group of users for specific tasks. Our novel proposed network flow priority management based on ML and SDN fulfills high control to give the required flow priority to SHE data traffic. The proposal relies on selected header bits from the traffic class field of a packet using the ML to prioritize traffic flows according to the precedence levels by governing the Differentiated Services Code Point (DSCP) bits in keeping with network administrator policies. The proposed network has been evaluated and performed utilizing the MATLAB platform and the Mininet simulator. The results of extensive testing show enhancement by applying our forcing priority algorithm obtained an efficient reduction in queuing delay and lost packets. The average waiting time in queue was reduced by around 61%, and the lost packets hit 0.005% when adopting the SDN-based ML network traffic priority management. 15 INDEX TERMS AI, DSCP, packet header, precedence level, SDN. I. INTRODUCTION 16 Nowadays, the world is experiencing natural terrible changes 17 and challenges besides terrorist threats. In order to prevent 18 or at least reduce the destructive effects of these disasters, 19 world countries need reliable and trusted communication net-20 works. Such special networks will help in saving the people 21 and the country's national security. Therefore, these special 22 networks have the highest traffic priority to ensure speed 23 response by responsible humans. To enable the forward-24 ing of Security, Health, and Emergency (SHE)'s data traffic 25 over Internet networks, this data traffic must be deported 26 and transferred through public telecommunication networks. 27 The associate editor coordinating the review of this manuscript and approving it for publication was Qingli Li. This process requires that communication networks include diverse and modern technologies such as Machine Learning (ML), Artificial Intelligence (AI) [1], and Software-Defined Networking (SDN) to attain the highest performance of these networks [2]. To guarantee efficient data transferring of SHE networks across the public Internet links, that needs to dedicate the highest priority for this data if these special networks fail in the wake of severe risks. The term ''special networks'' in this paper indicates that networks connect their users within a private and authenticated login to communicate with each other in close domain networks. As examples of such networks are Ad hoc [3], security or police, cellular, and health networks. However, some of these networks are considered confidential, secretive, and not available for public use. Therefore, there is restricted

In today's world, social media play an incredibly large role in the way the world exists in general. In this analysis introduce secure breached Social Networking security and hacked accounts to be protected. In the social networking site user want to reset or forgot their password on his social network account to using three Step Verification Systems using extremely protected. The first step secure using dialer secret password (color based click count) method and second step Password by own picture is a new graphical password system for social networking that restore the personal images typically used in graphical password systems with personalized sign. The proposed secure system used with personal pictures displayed end user device such as a mobile or desktop. The third one is to Authenticating users with the help of their friends (i.e., trustee-based social authentication) has been show into be a promising backup authentication mechanism. In this new social network security t...

Concerns have been expressed lately about content verification algorithms on social media platforms, resulting in data being presented to users or omitted from them. Twitter is one of those platforms that use this strategy, giving censorship strategies for specific content. The shadowban or practice of limiting content distribution without user acknowledgement is a current practice in online social networks, especially on Twitter. So, this paper is an AI Ethics position paper willing to expand the reflection about the impacts of programming artefacts on individual liberties in enterprise's Online social networks (OSN) to the computer science public. The conclusion to be drawn is that the limits of speech are to be imposed by the state after a properly democratic process took place [4]. The concern then turns into an international relations issue as it would be a threat for national sovereignty that one state, even inadvertently, regulates the actions of a communication enterprise on foreign states. Finally, the use of smart contracts is suggested as an alternative to be used by the base state for enforcing regulations on foreign OSNs.

The Internet of Vehicles (IoV), with advanced technology in 5G communication, is considered the backbone of a smart city's intelligent transport system. There are mainly two types of vehicular communication: (1) Vehicle to Vehicle (V2V) and (2) Vehicle to Infrastructure (V2I). In IoV, there is a dynamic change in the network topology according to the controllers, destination, vehicle movement, and road structure. Intelligent vehicles are assumed to work with the capacity of data processing, data storage devices, and communication devices to communicate with vehicles or Roadside InfraStructure (RSI). This article presents a post-quantum secure ring learning with error-based key exchange. This assumption ensures security against quantum attacks. The proposed design is an ant colony optimization-based ad hoc ordered distance vector routing algorithm that avoids suspicious vehicles in IoV broadcasting. The proposed framework consists of three parts: (i) certificate authority, (ii) suspicious vehicle detecting algorithm, and (iii) optimal path selection algorithm. The performance analysis section contains an analysis of the proposed design with related ones, and the proposed has better results.

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Mobile social networks (MSNs) have become increasingly popular in supporting many novel applications since emerging in the recent years. Their applications and services are of great interest to service providers, application developers, and users. This paper distinguishes MSNs from conventional social networks and provides a comprehensive survey of MSNs with regard to platforms, solutions, and designs of the overall system architecture. We review the popular MSN platforms and experimental solutions for existing MSN applications and services and present the dominant mobile operating systems on which MSNs are implemented. We then analyze and propose the overall architectural designs of conventional and future MSN systems. In particular, we present the architectural designs from two perspectives: from the client side to the server side, and from the wireless data transmission level to the terminal utilization level. We further introduce and compare the unique features, services, and key technologies of two generations of architectural designs of MSN systems. Then, we classify the existing MSN applications and propose one special form of MSN, i.e., vehicular social network, and demonstrate its unique features and challenges compared with common MSNs. Finally, we summarize the major challenges for ongoing MSN research and outline possible future research directions.

In recent years, The number of companies that have been collecting personal information for marketing purposes has grown. Then, they have been reselling it to other companies, banks, institutions. In this way, enterprises, financial and public institutions create huge collections of nonpublic data that are valuable information for taking marketing enterpises. By targetting appropriately profiled product and service offer at a selected group of receivers; trading partners and potential clients, a greater effectiveness used in the marketing strategy is achieved suitably Thereupon, multifaceted and informational personal data base, which are built in institutions, enterpises and social networking sites, become a valuable source of informaton used for the marketing purposes. The development of information processing and dissemination techniques through the Internet is determined by the many conveniences for beneficiaries, customers and users of services offered by the Internet. On the other hand, the development of information technologies on the Internet carries the risk of loss or theft of information by an unauthorized entities. The process of facilitating information online generates a number of threats related to identity theft, capturing nonpublic data by hackers, and accomplishing conversion of funds in the electronic system banking. In response to these threats, specific entities expand security systems for remote facilitating of information and making transactions via the Internet.

MP-TCP (MultiPath-Transmission Control Protocol) is a network protocol that uses subflows for allowing the existence of disjoint paths and increases the overall throughput with respect to employing a common TCP connection. The idea of analyzing MP-TCP messages using the principles of SDN (Software Defined Networking) is proposed. Relevant aspects of how the Analyzer was developed as a module for OpenDayLight’s SDN framework are presented. The Analyzer runs in the SDN controller and it commands the installation of appropriate rules in the network devices (switches supporting Openflow) so that all TCP traffic be derived to the controller. Then the Analyzer must identify MP-TCP messages by checking the options field of TCP and present all the related information to the user employing a GUI (Graphical User Interface). By combining the usage of proactive and reactive rules, the Analyzer’s implementation tries to minimize the impact of sending TCP traffic to the controller. The Analyzer h...

Social media websites are becoming more prevalent on the Internet. Sites, such as Twitter, Facebook, and Instagram, spend significantly more of their time on users online. People in social media share thoughts, views, and facts and create new acquaintances. Social media sites supply users with a great deal of useful information. This enormous quantity of social media information invites hackers to abuse data. These hackers establish fraudulent profiles for actual people and distribute useless material. The material on spam might include commercials and harmful URLs that disrupt natural users. This spam content is a massive problem in social networks. Spam identification is a vital procedure on social media networking platforms. In this paper, we have proposed a spam detection artificial intelligence technique for Twitter social networks. In this approach, we employed a vector support machine, a neural artificial network, and a random forest technique to build a model. The results in...

Vehicular ad-hoc network (VANET) is an advanced mobile wireless network. The escalation of equipped vehicles on the road grabs the attention of researchers and is constantly striving to take it further. This type of wireless network infrastructure helps to establish communication between vehicles. Roadside units, sensors, and vehicular nodes are the critical components of our work to protect the vehicular network. This research is focused on detecting and preventing fake vehicular nodes and their messages by applying fake node detection and prevention algorithms and counterfeit message detection and prevention algorithms. In our proposed approach, the fake node detection and prevention algorithms check the node profile after establishing the mesh structure. If the profile attribute named ''Pen/Rew'' satisfies the condition that should be less than or equal to a threshold value (zero), the fake message detection and prevention process starts. The message will be accepted once the situation is satisfied; otherwise, it is declared fake. We utilized ONE (opportunistic network environment) simulator to generate node movement models, route messages between nodes, and visualize mobility and messaging passing in real time. The results indicated that our proposed work perfectly detects and prevents fake nodes and messages.

This project was an investigation on the utilization of social media and academic performance of students in Geography in Nsit Atai Local Government Area of Akwa Ibom State, Nigeria. Four schools out of six public secondary schools in Nsit Atai Local Government Area were selected for the study. The population size was 1108 students, while the sample size was 100 students. The correlational research design was adopted for the study. The instruments for data collection were Social Media Utilization Questionnaire (SMUQ) and Geography Achievement Test (GAT). The instruments were validated by the supervisor and tested for reliability; a reliability coefficient of 0.78 was obtained using the test-retest method reliability test. Two research questions and null hypotheses, respectively were stated to guide the study. Data obtained from the students using the SMUQ and GAT were analyzed using the Pearson Product Moment Correlation Coefficient (PPMC).The hypotheses were tested at .05 alpha level of significance. Concerning the findings of this study, it was deduced that there was a fragile positive relationship between students' utilization of Whastapp, as well as Facebook social media and their academic performance in Geography. Based on the findings, it was recommended among others that social media utilization should be encouraged among students as this will help them develop excellent communication skills, build interactions, share ideas and enhance collaboration between students, teachers, and parents alike.

In this paper, performance evaluation of selected GSM networks in Nigeria is presented. The performance evaluation of the networks is based on requisite datasets pertaining to those networks and some key performance indicators (KPIs) which are applicable for Quality of Service (QoS) assessment of GSM networks. Specifically, seven (7) KPI parameters were computed, namely; Call Setup Success Rate (CSSR), Call Drop Rate (CDR), Standalone Dedicated Control Channel (SDCCH) congestion rate, Traffic Control Channel (TCC) congestion rate, Call Block Rate (CBR), Handover Success Rate (HOSR) and Handover Failure Rate (HOFR). The results show that from June, 2020 to May, 2022, MTN has the highest CSSR value of 99.73 % followed by Airtel with 99.41% then 9mobile with 99.19 % and Globacom 99.06 %. Also, MTN has lowest Call Drop Rate (CDR) value of 0.28, followed by Globacom with CDR value of 0.32, Airtel had CDR value of 0.35 and 9mobile had CDR value of 0.43. Again, only the network of MTN and Airtel have Standalone Dedicated Control Channel (SDCCH) < 0.2% as mandated by the Nigerian Communications Commission (NCC) while Globacom had SDCCH > 0.2% in October and 9mobile had SDCCH > 0.2% in about 13 month. In addition, Airtel, 9mobile, Globacom and MTN satisfied the NCC requirement of Traffic Control Channel (TCCH) ≤ 2%. Similarly, only Airtel and MTN have call blocked rate (CBR) ≤ 2.0% while Globacom exceeded 2% in October 2021 and 9mobile exceeded 2% in about 6months. Also, only MTN network was able to meet the Handover Success Rate (HOSR) ≥ 98 % requirement in all the months, while Airtel had HOSR < 98% for about 5 months, Globacom had HOSR < 98% for all the months and 9mobile had HOSR < 98% for about 17 months. In all, among the four GSM networks considered in the study, the best performance was recorded for the MTN network.

In the research of wireless communications, prototypes and measurements on real test-beds provide insights and fundamental information for a realistic tuning of simulation models. Recently there has been an increasing interest in exploring one of the critical fundamentals: the realistic radio range irregularity (RRI) model. This research builds on the IEEE 802.11, and investigates such a practical RRI model according to the measurements made under various settings. Using the RRI model, a set of representative localization algorithms are evaluated and compared. Through detailed analysis and extensive simulations, the paper points out how the localization performance is affected by the use of simplistic models. Moreover, some algorithms perfoming well under simplistic models do not work in real world settings. The RRI model reflects and highligths the weaknesses of those algorithms and allow the design of countermeasures. This paper introduces a constrained-greedy forwarding radio propagation method to remedy the negative effects encountered under actual operating environments.

Evolution is the essence of impact left behind by every being, every technology. We have well seen the advancements in the field of Computer Network i.e. from a simple Telegraph invented in 18th Century to 5G Communication on the verge of being implemented in South Korea. Needs of human beings never ceases to terminate, but they surely do result in invention of new technologies to pacify them. In this paper, we provide an overview on Generations of Networks along with a brief introspection on 5G technology that will provide access to wide range of telecommunication services in accordance with service demands in multiuser environment.

There have been efforts to investigate the effect of teaching by using mobile learning in university student's achievement. However, studies examining effect of teaching by using mobile learning in university students are, thus far, rare. This study adopted a quasi-experimental design with two types of teaching methods. One research group was assigned to the mobile learning teaching Method (n=25) and the other to the conventional teaching Method (n= 25). A multiple-choice test was developed in Unit introduces technology in course of pre-vocational education technology, Within the Bachelor of pre-vocational education program at Shobak university college. The results showed that the mobile learning teaching method was more effect than the conventional teaching method in the achievement of university students.

A social network consists of a group of people who share common interests and keep in contact with one another. This study examined the influence of engaging in mobile social networking on the sexual behavior of students of the University of Ibadan, Nigeria, at both undergraduate and postgraduate levels who are not more than 35 years of age. Sexual behaviours in the study are actual sexual involvement, safe sex practice and multiple sex partnership. The study also examined the relationship between identity, gratifications and Mobile social network use.
The study employed a sample survey research design which employed a structured questionnaire as instrument. A sample size of 500 students across the two levels of study was selected. This includes 314 undergraduates and 186 postgraduate students each with equal proportion of male and female. The research instrument was administered to 500 students and a total of 395 respondents returned it. Only 383 data collected from respondents met the inclusion criteria and were used for analysis.
Result of the logistic regression show that being sent i.e. receiving sexual content influences actual sexual involvement (B = 0.703, Exp (B) = 2.019, p < 0.05), average time of more than 10 hours influences safe sex practice (B = -1.328, Exp (B) = 0.265, p < 0.05), Being sent i.e. receiving sexual content influences multiple sexual partnership (B = 1.041, Exp (B) = 2.832, p < 0.05), living in the hostel influences safe sex practice (B = 1.343, Exp(B)) = 3.829, p < 0.05), demographic characteristics influences actual sexual involvement: being male (B = 1.157, Exp (B) = 3.181, p< 0.05), being undergraduate (B = -0.784, Exp (B)= 0.457, p < 0.05), demographic characteristics also influences multiple sexual partnership: being male (B = 1.746, Exp(B)= 5.731, p<0.05), being undergraduate (B = -1.085, Exp (B)= 0.338, p<0.05), living in the hostel (B = -1.054, Exp(B)= 0.349. p<0.05). Results of correlation analysis showed a positive correlation between social identity and receiving sexual content (rs = 0.145, N = 344, p < 0.05), and collective identity and frequency of sharing information (rs = 0.124, N = 350, p = 0.020). Results also show that the greatest gratification derived from Mobile social networks by respondents is being able to connect with friends. The descriptive and inferential analysis of data revealed that mobile social networking and its real life application influences all sexual behaviours considered and about 10% of respondents also declared that their sexual behavior has been influenced by mobile social networking.
This study concludes that interaction on mobile social networks influences sexual behaviours of young people. Sexuality educators should utilize MSN in providing sexuality education to young people.

Keywords: Social network, Social networking, Mobile social networking, Sexual behavior, adolescents, Young people.
 

Fake accounts on online social networks are increasing today with an increase in the number of active social network users. Social media websites allow users to share thoughts, facts, views and re-sharing these into various networks. Social media platforms provide users with enormous valuable information but with this great amount of information in social media, many issues like fake profile, online hacking have also grown. The fake profiles in online social sites create fake news and share unwanted material which contains spam links that affect natural users. The massive issue in social media communication networks is spam and it is necessary to identify fake profiles to stop spam. In this paper, a supervised machine learning algorithm called support vector machine (SVM) is used to identify fake accounts on social media effectively. In order to automatically identify fake online profiles, Random Forest classifier is used with SVM. With this concept, it can be applied online easily to identify millions of accounts that cannot be examined manually. The result of this model is compared with other identification techniques and the results show that the proposed algorithm performs better with high precision and recall. This method efficiently safeguards social media networks from online threats and attacks.

This project was an investigation on the utilization of social media and academic performance of students in Geography in Nsit Atai Local Government Area of Akwa Ibom State, Nigeria. Four schools out of six public secondary schools in Nsit Atai Local Government Area were selected for the study. The population size was 1108 students, while the sample size was 100 students. The correlational research design was adopted for the study. The instruments for data collection were Social Media Utilization Questionnaire (SMUQ) and Geography Achievement Test (GAT). The instruments were validated by the supervisor and tested for reliability; a reliability coefficient of 0.78 was obtained using the test-retest method reliability test. Two research questions and null hypotheses, respectively were stated to guide the study. Data obtained from the students using the SMUQ and GAT were analyzed using the Pearson Product Moment Correlation Coefficient (PPMC).The hypotheses were tested at .05 alpha lev...

This exploratory study investigates how a typically disadvantaged user group of older, female learners from rural, low-tech settings used and perceived a Facebook group as a research supervision and distance learning tool over time. The within-stage mixed-model research was carried out in a module of a part-time, advanced midwifery education course in rural South Africa. To address the research questions, three quantitative and qualitative surveys were repeated, pre, post, and three months post evaluation. The findings indicate that using the social media space lowered learners&#39; threshold to accessing educational resources. The increased ease of communication was afforded in particular by using mobile phones to access the space. The analysis also suggests that the social networking site became a more integral part of students&#39; learning environments. The learners&#39; use of the site to discuss further course and work-related issues increased during the intervention and also ...

In the research of wireless communications, prototypes and measurements on real test-beds provide insights and fundamental information for a realistic tuning of simulation models. Recently there has been an increasing interest in exploring one of the critical fundamentals: the realistic radio range irregularity (RRI) model. This research builds on the IEEE 802.11, and investigates such a practical RRI model according to the measurements made under various settings. Using the RRI model, a set of representative localization algorithms are evaluated and compared. Through detailed analysis and extensive simulations, the paper points out how the localization performance is affected by the use of simplistic models. Moreover, some algorithms perfoming well under simplistic models do not work in real world settings. The RRI model reflects and highligths the weaknesses of those algorithms and allow the design of countermeasures. This paper introduces a constrained-greedy forwarding radio propagation method to remedy the negative effects encountered under actual operating environments.

There has been tremendous growth in Global System for Mobile (GSM) services in Nigeria in the last two decade. The rapid development of GSM telecommunication industries have given rise to need for how the GSM services are delivered to customers efficiently. This paper is on GSM quality of service (QoS) performance in, Abuja Nigeria. The study investigates network transmission impairment and offers some useful remedies. The method involved use of Sony Ericson W-995 phone to gather data on physical network impairments in selected densely populated areas of Abuja. The data obtained were from four major GSM service providers MTN, Etisalat, Glo and Airtel. Assessment in terms of Key Performance Indicator (KPI) using Transmission Environment Monitory System (TEMS) Discovery professional software carried out on the networks under test. The results obtained from the analysis indicated that QoS performance of Airtel is slightly better than the other three GSM services providers tested within Nyanyan, Gwagwalada, and Wuse areas in Abuja. .

Thisstudyseekstofurthertheresearchononlinelanguagelearningbyexaminingthelevelatwhich intermediateESLstudentsunderstandandprocesssociopragmaticinformationintheirsecondlanguage (L2)ingloballynetworkedenvironmentslikeTwitter.Inthissemester-longstudy,L2Englishlearners fromavarietyoffirstlanguages(Chinese,Spanish,Arabic)analyzedauthenticEnglish-language tweetsproducedbywell-knownnativespeakers,withafocusonabbreviations,hashtagsandtweeter mood. Results revealed that high intermediate ESL students relied most heavily on word choice whenmakingsenseofEnglishtweets,demonstratingthatamajoritywereabletoextractsignificant meaningfromcommonabbreviations,prosifiedhashtags,indicesoftweetermoodandthetweet's largercontext.ThisinvestigationhighlightsTwitter'sstatusasanauthenticanddynamicL2setting thatfacilitatestheculturalenrichmentoflearnersandenhancestheirsocio-pragmaticawareness, whiledevelopingtheirmultiliteracyskillsinanL2.

Massive online social networks with hundreds of millions of active users are increasingly being used by Cyber criminals to spread malicious software (malware) to exploit vulnerabilities on the machines of users for personal gain. Twitter is particularly susceptible to such activity as, with its 140 character limit, it is common for people to include URLs in their tweets to link to more detailed information, evidence, news reports and so on. URLs are often shortened so the endpoint is not obvious before a person clicks the link. Cyber criminals can exploit this to propagate malicious URLs on Twitter, for which the endpoint is a malicious server that performs unwanted actions on the person's machine. This is known as a drive-by-download. In this paper we develop a machine classification system to distinguish between malicious and benign URLs within seconds of the URL being clicked (i.e. 'real-time'). We train the classifier using machine activity logs created while interacting with URLs extracted from Twitter data collected during a large global event-the Superbowl-and test it using data from another large sporting event-the Cricket World Cup. The results show that machine activity logs produce precision performances of up to 0.975 on training data from the first event and 0.747 on a test data from a second event. Furthermore, we examine the properties of the learned model to explain the relationship between machine activity and malicious software behaviour, and build a learning curve for the classifier to illustrate that very small samples of training data can be used with only a small detriment to performance.

This exploratory study investigates how a typically disadvantaged user group of older, female learners from rural, low-tech settings used and perceived a Facebook group as a research supervision and distance learning tool over time. The within-stage mixed-model research was carried out in a module of a part-time, advanced midwifery education course in rural South Africa. To address the research questions, three quantitative and qualitative surveys were repeated, pre, post, and three months post evaluation. The findings indicate that using the social media space lowered learners&#39; threshold to accessing educational resources. The increased ease of communication was afforded in particular by using mobile phones to access the space. The analysis also suggests that the social networking site became a more integral part of students&#39; learning environments. The learners&#39; use of the site to discuss further course and work-related issues increased during the intervention and also ...

Concerns have been expressed lately about content verification algorithms on social media platforms, resulting in data being presented to users or omitted from them. Twitter is one of those platforms that use this strategy, giving censorship strategies for specific content. The shadowban or practice of limiting content distribution without user acknowledgement is a current practice in online social networks, especially on Twitter. So, this paper is an AI Ethics position paper willing to expand the reflection about the impacts of programming artefacts on individual liberties in enterprise's Online social networks (OSN) to the computer science public. The conclusion to be drawn is that the limits of speech are to be imposed by the state after a properly democratic process took place [4]. The concern then turns into an international relations issue as it would be a threat for national sovereignty that one state, even inadvertently, regulates the actions of a communication enterprise on foreign states. Finally, the use of smart contracts is suggested as an alternative to be used by the base state for enforcing regulations on foreign OSNs.

Intelligent transportation systems use new technologies to improve road safety. In them, vehicles have been equipped with wireless communication systems called on-board units (OBUs) to be able to communicate with each other. This type of wireless network refers to vehicular ad hoc networks (VANET). The primary problem in a VANET is the quality of service (QoS) because a small problem in the services can extremely damage both human lives and the economy. From this perspective, this article makes a contribution within the framework of a new conceptual project called the Smart Digital Logistic Services Provider (Smart DLSP). This is intended to give freight vehicles more intelligence in the service of logistics on a global scale. This article proposes a model that combines two approaches—a Bayesian network and fuzzy logic for calculating the QoS in a VANET as a function of multiple criteria—and provides a database that helps determine the originality of the risk of degrading the QoS in...

Software Defined Networking (SDN) has attracted tremendous interest in the telecommunication industry due to its ability to abstract, manage and dynamically re-configure endto-end networks from a centralized controller. Though SDN is considered to be a suitable candidate for various use cases in mobile networks, none of the work so far has discussed its advantages and actual realization for Train-to-Wayside Communication System (TWC). In this paper, for the first time, the architecture and use cases of SDN controlled mobile backhauling framework for TWC is proposed. We discuss how our proposed architecture can efficiently handle mobility management and also provide dynamic quality-of-service (QoS) for different services on board. As a first step, a software prototype is developed using industrial standard OpenDayLight SDN controller to have our architecture evaluated. Since the automotive sector is being considered to be an important driver for 5G network, our SDN based mobile backhauling solution can be positioned in 5G where SDN plays an important role.

In the research of wireless communications, prototypes and measurements on real test-beds provide insights and fundamental information for a realistic tuning of simulation models. Recently there has been an increasing interest in exploring one of the critical fundamentals: the realistic radio range irregularity (RRI) model. This research builds on the IEEE 802.11, and investigates such a practical RRI model according to the measurements made under various settings. Using the RRI model, a set of representative localization algorithms are evaluated and compared. Through detailed analysis and extensive simulations, the paper points out how the localization performance is affected by the use of simplistic models. Moreover, some algorithms perfoming well under simplistic models do not work in real world settings. The RRI model reflects and highligths the weaknesses of those algorithms and allow the design of countermeasures. This paper introduces a constrained-greedy forwarding radio propagation method to remedy the negative effects encountered under actual operating environments.