Academic submissions (CoCIS)

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    A web-based system for reporting and creating awareness about social media threats and crime in Uganda
    ( 2023-01-06) Haguma, Jimmy
    The Internet is increasingly becoming a significant tool for social, economic, and human rights development in Uganda and Africa at large. Average citizens, human rights activists, civil society organizations, media houses, and more recently, politicians and government institutions, have resorted to the use of various forms of social media platforms in particular Facebook, WhatsApp and Twitter - for expression, association and information sharing. In countries such as Uganda, which is haracterized by high rates of unemployment, wage inequality and poverty, social media crime is attractive, easy and cheap with the fact that anybody with access to the internet could become a social media perpetrator. Social media crimes cannot be sufficiently investigated using traditional methods of recording lengthy statements, visiting the scene of crime, submitting the file to the Resident State Attorney for perusal, compelling witnesses to court, obtaining expert opinions from computer experts and tracing for suspects. Furthermore, there is a deficiency in the numbers and capabilities of law enforcement officers to investigate computer related crimes since such occur randomly in any part of the country with access to the internet. The main objective of this project was to develop a web-based system for reporting and creating awareness about social media threats and crime in Uganda. The study followed an agile methodology which included: Systems Study, Systems Analysis and Design, systems implementation and finally systems testing and validation. Qualitative and quantitative data was collected from respondents through the use of questionnaires and Focus Group Discussions. The Information System was developed using open-source technologies namely: PHP and JavaScript running on MySQL database and the graphical user interface of the system running on HTML5 platform. As part of the case study, a total of 20 respondents were interviewed from law enforcement officers to investigate the needs of stakeholders of the proposed social media crime reporting and awareness system. The results show that implementation of the proposed system will solve the problem of social media crime awareness since it is able to integrate and merge data from different sources. Therefore, the web-based system for reporting and creating awareness about social media threats and crime will be one of the solutions to reduce the social media crimes and increase awareness about social media crime in Uganda.
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    A framework for information management in E-agriculture
    (Makerere University, 2022-12-20) Mugejjera, Emmanuel
    Agriculture is a vital sector in a developing economy like Uganda’s. ICTs have been used in this sector to avail information and to support different information based agricultural processes in what is called electronic agriculture. Despite the use of ICTs, access to agricultural advisory information in a developing economy like Uganda’s remains problematic. This state of affairs is attributed to inadequate management of agricultural advisory information in e-agriculture. Therefore, this study aimed to develop a framework for supporting management of agricultural advisory information for small scale farmers engaged in growing of crops aided by ICTs in Uganda’s developing economy. The Design Science research method was used to guide the development of this framework. The framework presented in this work was based on a field study using 386 respondents from Uganda’s districts of Gulu, Lira, Mbale, Namayingo, Masaka, Wakiso, Mbarara and Ntungamo. Structural equation modeling was used in the design of the framework. The results show that the critical success factors for management of agricultural advisory information are: People and Technology; Funding, Processes, and Regulations; and Information use outcomes and continuity. The framework is composed of the above factors with People and Technology; Funding, Processes, and Regulations; influencing Information use outcomes and continuity. The framework was evaluated by seeking expert opinion and using a prototype in form of a web-based platform. In conclusion, the findings indicate that the framework is suitable for supporting the management of agricultural advisory information based on the parameters of goal, environment, structure, activity and evolution. It is suggested that the framework be used based on practical suggestions provided on each sub factor of the framework to aid policy makers in information management in e-agriculture support the agricultural advisory information management practices. Overall, the framework can be used to inform the management of agricultural advisory information. The prototype developed is a foundation for automation of selected tasks in the management of information in e-agriculture in Uganda’s context.
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    A Link Fabrication Attack Mitigation Approach (LIFAMA) for software defined networks
    (Makerere University, 2022-11-17) Katongole, Joseph
    In software defined networks (SDN), the controller is a critical resource yet it is a potential target for attacks once compromised. The conventional Open Flow Discovery Protocol (OFPD) used in building the topology view by the controller has vulnerabilities that easily allow attackers to poison the network topology by creating fabricated links that can be used for malicious intent. OFDP makes use of the link layer discovery protocol (LLDP) to discover existing links. However, LLDP is not e cient in fabricated link detection. Existing approaches to mitigate this problem have focused on using passive approaches that depend on observing unexpected behaviour. Examples of such behaviour include link latency and packet patterns to trigger attack alerts. The problem with the existing solutions is that their implementation causes longer link discovery time. This implies that a dense SDN would su↵er from huge delays in the link discovery process. In this study, we propose a Link Fabrication Attack (LFA) Mitigation Approach (LiFAMA) which is an active mitigation approach and one that minimizes the link discovery time. The approach uses Link Layer Discovery Protocol (LLDP) packet authentication toghether with Keyed-Hash Based Message Authentication Code (HMAC) and a link verification database (PostgreSQL)that stores records of all known and verified links in the network. This approach has been implemented in an emulated SDN environment using Mininet and a Python based open source openflow (POX) controller. The results show that the approach detects fabricated links in SDN in real time and helps mitigate them. Additionally, the link discovery time of LiFAMA out competes that of an existing LFA mitigation approach.
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    Extraction content recommender model for a personalised e-learning environment based on learner’s course assessment feeds
    (Makerere University, 2022-11-24) Twijukye, Brian
    E-learning, also known as online learning or electronic learning, is the acquisition of knowledge through digital technologies and media. In most cases, it refers to a course, program or degree delivered completely online. There are many terms used to describe learning that is delivered online, via the internet, ranging from Distance Education, to computerized electronic learning, online learning, internet learning and many others. Most authors point that consideration of the learner profile (personality, preferences, knowledge, etc.), is an essential and an important element in achieving an efficient and successful teaching. Therefore, it is extremely delicate and difficult to achieve a personalized learning scenario for each learner in the traditional closed classroom. Searching and retrieving information on E-learning environment is inconvenient, inefficient and sometimes time consuming as it relays irrelevant information that requires much time for student to scrutinize it and make meaning out of it, and in this case there is no previous work that has covered how learner’s assessment feeds like uploaded file’s content while answering E-learning environment set course works and quizzes can be incorporated in the extraction content recommender model to create a personalised E-learning environment. The main purpose of this work was to develop a an extraction content recommender model for e-learning personalisation based on learner’s course assessment feeds, which will allow students to obtain results according to their profiles and interests without taking too much time on the E-learning environment while searching relevant information. And the simulation was conducted on the extraction content recommender model with three datasets user profile ,learner's course assessment feeds and E-learning domain resources, we found out that using assessments feeds with different topic discussions in it recommends the value with highest rates and more recommendations are observed on it and when it comes to performance the learner's course assessment feeds with more words and one topic discussion takes too much time to recommend compared to learner's course assessment feeds with few words and more topics discussion. In the future work will be able to enable of our model to extract more assessment feeds from more than one section of the learner uploaded pdf assessment feeds and filter extracted information to get more key words of different topic’s discussions.
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    Detecting money laundering using a pattern matching approach based on Rete Algorithm
    (Makerere University, 2020-09) Kiwanuka, Patrick Ivan
    Money laundering is the criminal practice of filtering funds gotten from illegal activities through a series of transactions so that the funds appear as proceeds from legal activities. Money laundering is a diverse, complex process and basically involves three independent steps namely placement - placing, layering, and integration. It mainly occurs within financial institutions and it is difficult to detect [1]. All financial institutions in Uganda are mandated by the Central Bank to have mechanisms in place for detecting money laundering activities. The Parliament of Uganda passed an Anti-Money Laundering Act Law in 2013 which criminalizes these activities. In addition to the above laws, many institutions have developed policies internally that help them in detecting money laundering activities. Money laundering can have negative effects on the economy of the countries such as loss of government tax revenue, driving up the cost of government due to the need for increased law enforcement to fight the vice, undermining the legitimate private sector and integrity of the financial markets since Money launderers often use front companies which co-mingle the proceeds of illicit with genuine ones. These front companies have access to substantial illicit funds, allowing them to subsidize front company products and services at levels well below market rates. The objective of this project was to develop and validate money laundering detection rules using rete pattern matching algorithm. Through case studies with core banking systems of two local banks and related systems, requirements were established to inform the design of the patterns linked to potential money laundering activities. These patterns informed the design of rules such as the Daily transactions limit and extended the existing rules with a dynamic scoring system where a threshold score combines a net laundering score at run time. A banking system prototype was developed using python and SQLite for the database. The designed rules were implemented using Jess rule engine and integrated into the prototype banking core system. The system integrates dynamic rules making it hard for criminals to deduce the transactional limits. A scoring system has been introduced which evaluates each transaction against all the rules and categorizes it based on the overall score. This reduces on the number of false positives. Jess wrapped in Java was used to develop the improved rule sets and a scoring system that detected suspicious transaction patterns. Several transactions were carried out using the banking applications and suspicious transactions were highlighted by the system.