Masters Degrees (Information Science)

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Now showing 1 - 5 of 258
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    The entrepreneurship ecosystem of Botswana : a multi-dimensional case description
    (Stellenbosch : Stellenbosch University, 2024-03) Mahalelo, Rebanyana Meme; Maasdorp, Christiaan Hendrik; Stellenbosch University. Faculty of Arts and Social Sciences. Dept. of Information Science.
    ENGLISH SUMMARY: The indisputable finding that all forms of entrepreneurship require a conducive entrepreneurship ecosystem to succeed has prompted scholars within the entrepreneurship ecosystem field to develop instruments that assess entrepreneurship ecosystems. The results of measuring entrepreneurship ecosystems highlight the changes required to improve entrepreneurship support. This thesis adapts the Multi-dimensional Entrepreneurship Ecosystem Scale (MEES) to evaluate Botswana’s entrepreneurial ecosystem. The theoretical framework used to guide this thesis is the Isenberg entrepreneurship ecosystem framework, which models an ecosystem into six domains. This framework allows us to discuss the entrepreneurship ecosystem of Botswana, thus painting a picture of current entrepreneurship support provided by the six domains of Isenberg’s entrepreneurship ecosystem (finance, policy, culture, supports, markets, and human capital). To measure Botswana’s entrepreneurship ecosystem, the thesis employs qualitative research methods to collect perceptual data. Semi-structured interviews created from adapting the MEES are used to get perceptions of entrepreneurs and ecosystem key informants regarding entrepreneurship support, and a content analysis of course offerings in tertiary institutions using an Entrepreneurship Education Program (EEP) framework is undertaken to measure the provision of entrepreneurship education. The analysis of the thesis findings indicates that the domains of Botswana’s entrepreneurship ecosystem are not entirely conducive to entrepreneurship growth. An analysis of individual domains is provided, and recommendations are provided to policymakers and stakeholders within Botswana’s entrepreneurship ecosystem domains to enable the improvement of their government ministries or institutions in support of productive entrepreneurship. This research paper also helps close the knowledge gap of the Botswana government’s Vision 2036 transformation strategy supporting entrepreneurship towards a knowledge-based economy but lacking information regarding the conduciveness of its entrepreneurship ecosystem domains, i.e., where its ecosystem domains lack and how they should be improved to support entrepreneurship.
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    The role of traditional knowledge in a developing society : a case study of the relationship between traditional and scientific methods of detecting underground water in Botswana
    (Stellenbosch : Stellenbosch University, 2024-03) Sono, Tshimologo Topo; Kinghorn, Johan; le Roux, Daniel; Stellenbosch University. Faculty of Arts and Social Sciences. Dept. of Information Science.
    ENGLISH SUMMARY: This research report explores the role of indigenous knowledge, specifically indigenous water knowledge, in a developing society using Botswana as a case study. The study is grounded in the theory of Indigenous Knowledge Systems which suggests that indigenous knowledge plays a crucial role in sustainable development and should be recognized and integrated into socioeconomic, political and cultural policies and practices. It adopts a multi-pronged case study design combining an extensive literature review on indigenous knowledge in Botswana from an empirical research perspective. The literature review critically evaluates the theoretical foundations and contextual understanding of indigenous knowledge systems, traditional water knowledge, and their significance in developing societies while analyzing the complex relationship between indigenous and scientific knowledge, and the challenges and benefits of integrating the two. The empirical study comprises a survey of 58 staff in the Department of Water and Sanitation and Water Utilities Corporation, and interviews with 10 traditional water dowsers. This three-pronged case study enables a detailed exploration of traditional water knowledge and practices in Botswana and perspectives on integrating these with scientific water management approaches. The findings from this study indicate the prevalence of traditional dowsing practices despite proliferation of scientific methods. While perceptions of the success rate of traditional dowsing are mixed, observed success of recognized dowsers has provided evidence of efficacy, to some great extent. The study also reveals that there is limited collaboration between water authorities and traditional dowsers. However, most survey respondents supported combining traditional and scientific methods, recognizing the value of diverse body of knowledge systems. There was an observed trend that picked that views differed on whether traditional knowledge is equivalent, complementary, or inferior to scientific knowledge. As such, it emerges that there are key opportunities that exist for greater recognition of traditional knowledge in policies, training and resources to improve scientific practice, participatory water management approaches, and fostering respectful collaboration between traditional and scientific knowledge holders. However, challenges remain regarding the verification of traditional knowledge, conflicts between knowledge systems, and changes to cultural practices. The study concludes that integrating traditional water knowledge with scientific approaches can enhance the effectiveness and sustainability of water management in Botswana; nevertheless, this requires concerted efforts across policy, practice, research, and education spheres. The findings provide valuable insights to guide these efforts and contribute to the broader global discourse on harnessing indigenous knowledge in developing societies.
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    Towards a supervised machine learning algorithm for cyberattacks detection and prevention in a smart grid cybersecurity system
    (Stellenbosch : Stellenbosch University, 2024-03) Banda, Takudzwa Vincent; Blaauw, Dewald; Watson, Bruce; Stellenbosch University. Faculty of Arts and Social Sciences. Dept. of Information Science.
    ENGLISH SUMMARY: Critical infrastructure cyberattacks have become a significant threat to national security worldwide. Adversaries exploit vulnerabilities in communication networks, technologies, and protocols of smart grid SCADA networks to gain access and control of power grids, causing blackouts. Despite the need to safeguard the reliable and stable operation of the grid against cyberattacks, simultaneously detecting and preventing attacks presents a significant challenge. To address this, a Kali Linux machine was connected to a smart grid SCADA network simulated in GNS3 to perform common cyberattacks. Wireshark was then deployed to capture network traffic for machine learning. Aiming to improve the detection and prevention of cyberattacks the study proposed a dual-tasked ensemble supervised machine learning model, a combination of Multi-Layer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost), that had an average accuracy of 99.60% and detection rate of 99.48%. The first task of the model distinguishes between normal state and cyberattack modes of operation. The second task prevents suspicious packets from reaching the network destination devices. Leveraging the PowerShell command-line tool, to success the model dynamically applies packet filtering firewall rules based on its predictions. Therefore, the proposed model is both an Intrusion Detection System (IDS) and Intrusion Prevention System (IPS). The model was tested on new data, producing an accuracy of 99.19% and detection rate of 98.95%. Furthermore, the model's performance was compared to existing proposed cyber-attack detection models and consistently outperforms these proposed models on most datasets, demonstrating its superiority in terms of precision, accuracy, and recall/detection rate. Thus, the proposed model, with its function as a firewall, enhances the overall security capabilities of the smart grid SCADA networks and significantly mitigates potential cyberattacks.
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    An investigation and analysis of vulnerabilities surrounding cryptocurrencies and blockchain technology
    (Stellenbosch : Stellenbosch University, 2024-03) Heyl, Isabelle Christina; Blaauw, Dewald; Watson, Bruce; Stellenbosch University. Faculty of Arts and Social Sciences. Dept. of Information Science.
    ENGLISH SUMMARY: As individuals search for a safe and alternative payment method, the popularity of cryptocurrencies and blockchain technology continues to grow. Despite their benefits, the increasing prevalence of these technologies also exposes them to a higher risk of encountering potential threats. These threats stem from the vulnerabilities and technical limitations within, which in turn, influences its potential to be adopted across different industries. Through a quantitative approach, this paper aims to detect and mitigate the vulnerabilities and technical limitations within cryptocurrencies and blockchain. A simulated environment provides the means to study distinct parameters within a Bitcoin network, particularly in the event of a double-spending and selfish mining attack. Based on the findings, the success rate and revenue of the attacker were primary influenced by the network’s stale block rate, the attacker’s hash rate and the double-spend value. Moreover, there is a significant difference in the parameters pre- and post-attacks. It is evident that the block size has a considerable effect on the parameters in the network. As such, a single-objective problem is solved to determine what the optimal block size should be to minimize the block generation time and block delay time, seeking to reduce the overall latency and increase the throughput. It can be concluded that using the optimal block size can partially reduce the threat of double-spending attacks, but not eliminate it completely. It becomes evident that other mitigation schemes should be implemented to overcome these vulnerabilities.
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    The impact of using a contract-driven, test-interceptor based software development approach
    (Stellenbosch : Stellenbosch University, 2023-12) Posthuma, Arend Justus; Solms, Fritz; Watson, Bruce; Stellenbosch University. Faculty of Arts and Social Sciences. Dept. of Information Science.
    ENGLISH SUMMARY: Contract Driven Development, also known as Design by Contract (DBC), Contract Programming and Programming by Contract, is a well-known methodology for designing software. The main aim of the methodology is to reduce quality assurance costs, and to improve reusability and software quality through the use of formalized component contracts. Companies are spending large amounts of money and resources on quality assurance and testing in the pursuit of correct and bug-free software, yet contract driven development is not currently used extensively in industry. This is because the specification of formalized component requirements within component contracts is perceived to be complex, tedious and expensive. In this study, we introduce the concept of test-interceptors, which are automatically generated from component contracts. The function of the testinterceptors is to validate whether, in the context of rendering component services, the component contracts are satisfied. These test interceptors can be used for unit testing, integration testing, operational testing and external service provider oversight. It is expected that such an approach improves verifiability, enforces separation of test logic and test data and assists with recuperating part of the requirements formalization costs through lower test development costs and lower costs associated with bug fixes. This study aims to assess the impact of introducing contract-driven development to both, the quality attributes of the software development process, and the quality of the software produced by the process.