Evaluation of Key Security Issues Associated with Mobile Money Systems in Uganda

This research article published by MDPI, 2020Smartphone technology has improved access to mobile money services (MMS) and successful mobile money deployment has brought massive benefits to the unbanked population in both rural and urban areas of Uganda. Despite its enormous benefits, embracing the usage and acceptance of mobile money has mostly been low due to security issues and challenges associated with the system. As a result, there is a need to carry out a survey to evaluate the key security issues associated with mobile money systems in Uganda. The study employed a descriptive research design, and stratified random sampling technique to group the population. Krejcie and Morgan’s formula was used to determine the sample size for the study. The collection of data was through the administration of structured questionnaires, where 741 were filled by registered mobile money (MM) users, 447 registered MM agents, and 52 mobile network operators’ (MNOs) IT officers of the mobile money service providers (MMSPs) in Uganda. The collected data were analyzed using RStudio software. Statistical techniques like descriptive analysis and Pearson Chi-Square test was used in data analysis and mean (M) > 3.0 and p-value < 0.05 were considered statistically significant. The findings revealed that the key security issues are identity theft, authentication attack, phishing attack, vishing attack, SMiShing attack, personal identification number (PIN) sharing, and agent-driven fraud. Based on these findings, the use of better access controls, customer awareness campaigns, agent training on acceptable practices, strict measures against fraudsters, high-value transaction monitoring by the service providers, developing a comprehensive legal document to run mobile money service, were some of the proposed mitigation measures. This study, therefore, provides a baseline survey to help MNO and the government that would wish to implement secure mobile money systems

Investigating the Usability and Quality of Experience of Mobile Video-Conferencing Apps Among Bandwidth-Constrained Users in South Africa

In response to Covid-19 and global lockdowns, we have seen a surge in video-conferencing tools' usage to enable people to work from home and stay connected to family and friends. Although understanding the performance and the perceived quality of experience for users with bandwidth caps and poor internet connections could guide the design of video-conferencing apps, the usability of video-conferencing applications have been severely overlooked in developing countries like South Africa, where one-third of adults rely on mobile devices to access the internet and where the per-gigabyte data cost is some of the most expensive in Africa. Considering these numbers, we conduct a two-prong study where 1) we measure bandwidth consumption of different Android apps through bandwidth measurement experiments and 2) we conduct interviews with bandwidth-constrained users to better understand their perceptions of mobile videoconferencing apps. The key benefit of this study will be to inform organisations that seek to be inclusive about these tools' relative usability by letting them know about the factors influencing users' quality of experience

Computational Analysis of Urban Places Using Mobile Crowdsensing

In cities, urban places provide a socio-cultural habitat for people to counterbalance the daily grind of urban life, an environment away from home and work. Places provide an environment for people to communicate, share perspectives, and in the process form new social connections. Due to the active role of places to the social fabric of city life, it is important to understand how people perceive and experience places. One fundamental construct that relates place and experience is ambiance, i.e., the impressions we ubiquitously form when we go out. Young people are key actors of urban life, specially at night, and as such play an equal role in co-creating and appropriating the urban space. Understanding how places and their youth inhabitants interact at night is a relevant urban issue. Until recently, our ability to assess the visual and perceptual qualities of urban spaces and to study the dynamics surrounding youth experiences in those spaces have been limited partly due to the lack of quantitative data. However, the growth of computational methods and tools including sensor-rich mobile devices, social multimedia platforms, and crowdsourcing tools have opened ways to measure urban perception at scale, and to deepen our understanding of nightlife as experienced by young people. In this thesis, as a first contribution, we present the design, implementation and computational analysis of four mobile crowdsensing studies involving youth populations from various countries to understand and infer phenomena related to urban places and people. We gathered a variety of explicit and implicit crowdsourced data including mobile sensor data and logs, survey responses, and multimedia content (images and videos) from hundreds of crowdworkers and thousands of users of mobile social networks. Second, we showed how crowdsensed images can be used for the computational characterization and analysis of urban perception in indoor and outdoor places. For both place types, urban perception impressions were elicited for several physical and psychological constructs using online crowdsourcing. Using low-level and deep learning features extracted from images, we automatically inferred crowdsourced judgments of indoor ambiance with a maximum R2 of 0.53 and outdoor perception with a maximum R2 of 0.49. Third, we demonstrated the feasibility to collect rich contextual data to study the physical mobility, activities, ambiance context, and social patterns of youth nightlife behavior. Fourth, using supervised machine learning techniques, we automatically classified drinking behavior of young people in an urban, real nightlife setting. Using features extracted from mobile sensor data and application logs, we obtained an overall accuracy of 76.7%. While this thesis contributes towards understanding urban perception and youth nightlife patterns in specific contexts, our research also contributes towards the computational understanding of urban places at scale with high spatial and temporal resolution, using a combination of mobile crowdsensing, social media, machine learning, multimedia analysis, and online crowdsourcing

The InclusiveMag Method: A Start Towards More Inclusive Software for Diverse Populations

How can software practitioners assess whether their software supports diverse users? Although there are empirical processes that can be used to find “inclusivity bugs” piecemeal, what is often needed is a systematic inspection method to assess software’s support for diverse populations. To help fill this gap, this thesis introduces InclusiveMag, a generalization of GenderMag that can be used to generate systematic inclusiveness methods for a particular dimension of diversity. We then present 1) a multicase study covering eight diversity dimensions, of eight teams’ experiences applying InclusiveMag to eight under-served populations and their “mainstream” counterparts and 2) the start of the application of InclusiveMag to making software more inclusive to individuals of low socioeconomic status, through means of a systematic mapping study

Machine Learning in Image Analysis and Pattern Recognition

This book is to chart the progress in applying machine learning, including deep learning, to a broad range of image analysis and pattern recognition problems and applications. In this book, we have assembled original research articles making unique contributions to the theory, methodology and applications of machine learning in image analysis and pattern recognition

Educational Technology and Related Education Conferences for June to December 2015

The 33rd edition of the conference list covers selected events that primarily focus on the use of technology in educational settings and on teaching, learning, and educational administration. Only listings until December 2015 are complete as dates, locations, or Internet addresses (URLs) were not available for a number of events held from January 2016 onward. In order to protect the privacy of individuals, only URLs are used in the listing as this enables readers of the list to obtain event information without submitting their e-mail addresses to anyone. A significant challenge during the assembly of this list is incomplete or conflicting information on websites and the lack of a link between conference websites from one year to the next

Development of a secure multi-factor authentication algorithm for mobile money applications

A Thesis Submitted in Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Information and Communication Science and Engineering of the Nelson Mandela African Institution of Science and TechnologyWith the evolution of industry 4.0, financial technologies have become paramount and mobile money as one of the financial technologies has immensely contributed to improving financial inclusion among the unbanked population. Several mobile money schemes were developed but, they suffered severe authentication security challenges since they implemented two-factor authentication. This study focused on developing a secure multi-factor authentication (MFA) algorithm for mobile money applications. It uses personal identification numbers, one-time passwords, biometric fingerprints, and quick response codes to authenticate and authorize mobile money subscribers. Secure hash algorithm-256, Rivest-Shamir-Adleman encryption, and Fernet encryption were used to secure the authentication factors, confidential financial information and data before transmission to the remote databases. A literature review, survey, evolutionary prototyping model, and heuristic evaluation and usability testing methods were used to identify authentication issues, develop prototypes of native genuine mobile money (G-MoMo) applications, and identify usability issues with the interface designs and ascertain their usability, respectively. The results of the review grouped the threat models into attacks against privacy, authentication, confidentiality, integrity, and availability. The survey identified authentication attacks, identity theft, phishing attacks, and PIN sharing as the key mobile money systems’ security issues. The researcher designed a secure MFA algorithm for mobile money applications and developed three native G-MoMo applications to implement the designed algorithm to prove the feasibility of the algorithm and that it provided robust security. The algorithm was resilient to non-repudiation, ensured strong authentication security, data confidentiality, integrity, privacy, and user anonymity, was highly effective against several attacks but had high communication overhead and computational costs. Nevertheless, the heuristic evaluation results showed that the G-MoMo applications’ interface designs lacked forward navigation buttons, uniformity in the applications’ menu titles, search fields, actions needed for recovery, and help and documentation. Similarly, the usability testing revealed that they were easy to learn, effective, efficient, memorable, with few errors, subscriber satisfaction, easy to use, aesthetic, easy to integrate, and understandable. Implementing a secure mobile money authentication and authorisation by combining multiple factors which are securely stored helps mobile money subscribers and other stakeholders to have trust in the developed native G-MoMo applications

The mediating role of organizational reputation and trust in the intention to use wearable health devices : cross-country study

BACKGROUND : The use of consumer wearable health devices for fitness tracking has seen an upward trend across the globe. Previous studies have shown that trust is an important factor in the adoption and use of new technologies. However, little is known about the influence of organizational reputation and trust on the intention to use wearable health devices. OBJECTIVE : This study aimed to investigate the mediating role of organizational reputation and trust in the intention to use wearable health devices and to examine the extent to which the country of residence influenced the effect of organizational reputation on consumers’ trust in and intention to use wearable health devices. METHODS : We conducted a cross-country survey with participants from Kenya and South Africa using a Google Forms questionnaire derived from previously validated items. A series of mediation regression analyses were carried out using the PROCESS macro with the bootstrap CI procedure. A one-way, between-group multivariate analysis of variance (MANOVA) was also used to determine the key factors that distinguish Kenyans and South Africans in their intention to use wearable health devices. RESULTS : A total of 232 questionnaire responses were collected. The results revealed that organizational reputation significantly mediates the relationship between trust propensity and trust, with an indirect effect of 0.22 (95% CI 0.143-0.309). Organizational reputation also plays a significant direct role in the intention to use a wearable health device, with a direct effect of 0.32 (95% CI 0.175-0.483). This role is regardless of participants’ country of residence. Furthermore, there is a significant mediating effect of trust on the relationship between trust propensity and the intention to use a wearable health device, with an indirect effect of 0.26 (95% CI 0.172-0.349); between perceived security and the intention to use a wearable health device, with an indirect effect of 0.36 (95% CI 0.255-0.461); and between perceived privacy and the intention to use a wearable health device, with an indirect effect of 0.42 (95% CI 0.282-0.557). The MANOVA test shows statistically significant differences in all variables for both groups, with the exception of organizational reputation where there is no significant difference between the two cohorts. CONCLUSIONS : Organizational reputation has a significant direct influence on participants’ trust in and the intention to use a wearable health device irrespective of their country of residence. Even in the presence of perceived security and perceived privacy, trust has a significant mediating effect on the intention to use a wearable health device.Multimedia Appendix 1 Research model.Multimedia Appendix 2 Research instrument.Multimedia Appendix 3 Mediating role of organizational reputation in the relationship between trust propensity and trust, with regression coefficients, indirect effects, and bootstrapped CI.Multimedia Appendix 4 Mediating role of trust in the relationship between trust propensity and intention to use wearable health devices, with regression coefficients, indirect effects and bootstrapped CI.Multimedia Appendix 5 Mediating role of trust in the relationship between organization reputation and intention to use wearable health devices, with regression coefficients, indirect effects, and bootstrapped CI.Multimedia Appendix 6 Mediating role of trust in the relationship between perceived security and intention to use wearable health devices, with regression coefficients, indirect effects and bootstrapped CI.Multimedia Appendix 7 Mediating role of trust in the relationship between perceived privacy and intention to use wearable health devices, with regression coefficients, indirect effects and bootstrapped CI.The Department of Informatics and the University of Pretoria.http://mhealth.jmir.orgam2020Informatic

Introduction to Development Engineering

This open access textbook introduces the emerging field of Development Engineering and its constituent theories, methods, and applications. It is both a teaching text for students and a resource for researchers and practitioners engaged in the design and scaling of technologies for low-resource communities. The scope is broad, ranging from the development of mobile applications for low-literacy users to hardware and software solutions for providing electricity and water in remote settings. It is also highly interdisciplinary, drawing on methods and theory from the social sciences as well as engineering and the natural sciences. The opening section reviews the history of “technology-for-development” research, and presents a framework that formalizes this body of work and begins its transformation into an academic discipline. It identifies common challenges in development and explains the book’s iterative approach of “innovation, implementation, evaluation, adaptation.” Each of the next six thematic sections focuses on a different sector: energy and environment; market performance; education and labor; water, sanitation and health; digital governance; and connectivity. These thematic sections contain case studies from landmark research that directly integrates engineering innovation with technically rigorous methods from the social sciences. Each case study describes the design, evaluation, and/or scaling of a technology in the field and follows a single form, with common elements and discussion questions, to create continuity and pedagogical consistency. Together, they highlight successful solutions to development challenges, while also analyzing the rarely discussed failures. The book concludes by reiterating the core principles of development engineering illustrated in the case studies, highlighting common challenges that engineers and scientists will face in designing technology interventions that sustainably accelerate economic development. Development Engineering provides, for the first time, a coherent intellectual framework for attacking the challenges of poverty and global climate change through the design of better technologies. It offers the rigorous discipline needed to channel the energy of a new generation of scientists and engineers toward advancing social justice and improved living conditions in low-resource communities around the world