MSIT Theses and Dissertations (2019)

Permanent URI for this collection

http://hdl.handle.net/11071/6621

Browse

Recent Submissions

Now showing 1 - 5 of 25
  • Thumbnail Image
    Item
    Emergency response system based on an intelligent and optimal route finder
    (Strathmore University, 2019) Ngunjiri, Kiere Peter
    Road accidents have become a significant cause of injuries and death in developing countries. Every year, the lives of more than 1.25 million people around the world are cut short as a result of this road traffic crash menace. Approximately 20 to 50 million more people suffer non-fatal injuries, with which many incur disability as a result of their injury. Road traffic injuries cause considerable economic losses to individuals, their families, and the nations as a whole. These losses arise from the cost of treatment as well as lost productivity for those killed or disabled by their injuries, and for family members who need to take time off work or school to care for the injured. Road traffic crashes cost most countries 3% of their gross domestic product. Reports show that one of the best ways to reduce this fatalities and disabilities from these crashes is by decreasing the casualty evacuation time; this is the timely and efficient movement including en route care provided by medical personnel to injured patients evacuated from the scene of an accident to receiving medical facilities. This research aims at improving the evacuation process in order to reduce the fatalities as well as the impact of the injuries achieved by helping the public have access to specialized equipment and vehicles in aid of disaster and accident management. The purpose of this research has put more focus on ambulance access for patients in critical condition by designing a web-based program that can be accessed from a mobile phone or computer to inform the closest located ambulance to respond to distress calls. Also, there was need to help the ambulance drivers' get to the nearest hospital using the shortest and fastest route, which would be term as the most convenient route. The framework designed helps the patients who need emergency care attended to and their lives put out of danger as fast as possible for further medical attention. The framework also provides the emergency response unit with a platform to get fully reimbursed after delivery of services. An extensive literature review was carried out to determine the impact of delayed emergency response to patients in critical condition and addressed the problem through the development of a system that eliminates unnecessary delays.
  • Thumbnail Image
    Item
    A Phishing detection model based on dynamic-hybrid feature selection
    (Strathmore University, 2019-07) Ruiru, Daniel K
    Phishing attacks have been a big internet nuisance since the early 1990s when hackers started stealing information from organizations using messaging platforms. At the time, the problem affected large institutions and corporations as the internet was still in its early stages of development and, had minimal individual subscribers. The early 2000s saw the widespread application of the technology (internet) which subsequently saw phishers target individual users using electronic mails (emails). In itself, phishing is a form of cyber-attack that steals personal information from unsuspecting users by duping them using verification or reward emails. This deception process ultimately helps the intruders to access sensitive data that can be used to access financial records for monetary gains or identity theft. Phishing attacks are so prevalent today that over 95 percent of all cyber-attacks are characterized by their intrusion procedures. Moreover, the attacks seem to increase each year and based on recent surveys are said to have a 60 percent annual growth rate. It is because of this outcome that this research proposes a predictive model to detect phishing attacks by implementing a system that pre-empts the intrusion processes before they happen. Unlike conventional methods that rely on human expertise to mitigate the problem, the proposed model automates the identification of the attacks and subsequently their control. This research aims to achieve this goal by optimizing the selection of subset features using a dynamic model that analyses the structural properties of phishing attacks to get adaptive attributes (features) for detecting phishing threats (as highlighted in chapter 4). Random forest is then used as the final classifier owing to its accuracy results (84.13%). Ultimately, the study then proposes the construction of a base model for bootstrapping other detection models in the cyber-security world.
  • Thumbnail Image
    Item
    An Automatic soiled linen detection prototype for hospital ward caregivers
    (Strathmore University, 2019) Akumonyo, Lidonde James
    The well-being of a hospital patient is highly prioritized by the provision of a clean and safe environment with the aim of improving the rate of patient’s recovery. Continuous patients’ checks and alert mechanisms are essential to the caregiver in aiding them to ensure a clean and safe environment is maintained for the patient receiving medical care from the facility. The existing system used relies on scheduled visits done by nurses during their shifts to assess the nature of the patients whilst assisting them where necessary. This process is usually cumbersome and prone to neglect which leads to patients getting new hospital-acquired infections. In other cases, the unpredictable nature of patient’s condition may result to high incontinence where the patient may soil linen more frequently due to deterioration of their health condition and this would need to have the caregiver promptly notified when such an event occurs to have the patient linen changed. With this challenge experienced, the study aims to come up with a solution termed as a soiled linen detection prototype to alert hospital ward caregivers of soiled linen. During this process, the researcher employed the use of experimental research to determine the variables essential in soiled linen detection. Together with this prototyping and use of questionnaires were employed to fine tune the system into meeting the users’ requirement as a solution to soiled linen detection challenge. The solution created integrates the idea of IoT with Wireless Sensor Networks. Hospital beds will be attached to humidity and gas sensors that are connected to the IoT device. The bedlinen will cover the sensors and they will transmit the hydrogen sulphide gas levels and humidity levels to the central cloud storage system whenever the safety levels have been exceeded. Upon successfully sending of the information from the IOT equipment the web application automatically picks data entry made to the cloud database storage and displays it on the client GUI awaiting to be handled by the caregiver. The client app GUI is used by the assigned caregiver and the nurse at the central ward station to notify and locate the bed that requires attention allowing proactive response to the patient who requires bedlinen change. The results of this was a prompt notification soiled linen prototype that was able to give notification as soon as the gas and humidity levels were exceeded
  • Thumbnail Image
    Item
    A Real time electricity usage monitoring system using smart meters for wastage detection in Kenya
    (Strathmore University, 2019) Obonyo, Joseph Oduor
    Electricity utilities face dual challenges of generation and distribution. While many utilities are now migrating their operations into modern digitized platforms, most of these utilities have had to rely on old systems to carry out and monitor their commercial activities such as connectivity activity, itinerary scheduling, meter and device management, cycle billing, collections management and management reporting. This is causing utilities to reimagine customer engagements with a focus on feedback, put in place loss detection systems in their grids, use predictive models to schedule maintenance and other asset-management activities, equipping field workers with mobile devices that let them access technical instructions while in the field and deploy customized systems to help manage the extending networks. The main focus of this study was to design a real time electricity usage detection system using smart meters in Kenya, a system that would aid utility companies in providing real time feedback for service provision and anomaly detection. This research was done using smart meters to remotely record usage and record those messages manually into a web based portal. While it was not possible to replace existing old meters with the smart meters, the study made use of a test kit to simulate power consumption and usage recording. This study has put in place a model system that can be remotely connected to a smart meter and feedback generated in real time
  • Thumbnail Image
    Item
    A System to detect suspicious activities in network traffic
    (Strathmore University, 2019) Gesare, Roselyne Magangi
    Modern enterprise networks have become targets of attacks from Internet malware including worms, self-propagating bots, spamming bots, client-side infects (drive-by downloads) and phishing attacks. The results of a cyber-attack which include loss of company information, theft of money, costs of repairing the affected systems and perhaps damage to the reputation of the organization, can be devastating. However, with the right tools, security can dissect suspicious traffic to detect these attacks. When a company institutes a good method of network security surveillance, security analysts could be alerted within minutes of problems occurring in good time. It is with this aim that this study sought to research and develop a simple and robust system that could be used to detect suspicious activities in network traffic. Specifically, the study sought to; Discuss and analyze suspicious activities in network traffic and devices; analyze the existing techniques used to detect suspicious activities in network traffic; develop a system for detecting suspicious activities in a network traffic; and validate the proposed system. The study adopted an experimental design. The experiment was conducted on an Ubuntu machine running 16.04 LTS where Snort was installed alongside PulledPork, Barnyard2 and BASE to act as the Web GUI. ICMP large packets were sent to the network for detection and the system was able to detect, analyze and report them on the BASE GUI. The target population for this study was network traffic. The researcher generated the network traffic through sending data packets across the networks. The network traffic was analyzed by using the network security tools analyzed by the researcher and chosen based on their availability and compatibility with one another to come with the desired setup. This research was not aimed at reinventing the wheel but offering major improvement through precise feedback on what network administrators across different organizations could identify as suspicious activities in their networks