Browsing by Author "Ndibwile, Jema"

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Automatic Escaped Animal Detection and Monitoring System: A Case study of Volcanoes National Park (VNP) in Rwanda
(ijasre, 2022-07) Zirakwiye, Innocent; Ndibwile, Jema; Michael, Kisangiri
The results have been shown that the people especially farmers living at the edge of Volcanoes National Park (VNP) practiced agricultural business due to the fertile soil found in the region. The rising number of agronomies in the zone, number of tourists, and illegal forest users such as poaching, and deforestation cause wild animals to get out of their habitats. Therefore, forest animals present a likely risk to damage crops whenever they get out of the forest. The current systems such as “Buffer Wall also known as wall of stones” was manually operated; electric fence systems resulted in death and pain to wild animals. The primary creation of this paper is to develop an Automatic Escaped Animal Detection and Monitoring System. Due to the development of automatic systems for detecting and monitoring all moving wild animals and intruders, it was stated that using automation at Buffer wall could be helpful for both wild animals and farmers keeping safe. The objectives of developing an Automatic Escaped Animal Detection and Monitoring System were to reduce the probability of crop raids, death and injuries between wild animals and farmers, warning the wild animals using of buzzer, speaker with a recorder voice of lion and block of LEDs to remain in their habitats and the notifications sent to the park officials related to the wild animals getting out of the forest. This system should primarily use sensing devices to detect and monitor their presence. The study reveals that the people especially farmers living at the edge of Volcanoes National Park (VNP) can be protected using this system. The specialty of this technological system developed was to automate manual and improve the current systems by using Arduino NANO Microcontroller to execute system’s operations, GPS NEO 6M for locating moving wild animal, Ultrasonic sensor for detecting wildlife and calculating its speed, PIR sensor to detect intruders, GSM SIM900 to notify park rangers, reduction of crop raiding, and finally reducing the death and pain of wild animals caused by the current systems.
Detection of Username Enumeration Attack on SSH Protocol: Machine Learning Approach
(MDPI, 2021-11-17) Agghey, Abel; Mwinuka, Lunodzo; andhare, Sanket; Dida, Mussa; Ndibwile, Jema
Over the last two decades (2000–2020), the Internet has rapidly evolved, resulting in symmetrical and asymmetrical Internet consumption patterns and billions of users worldwide. With the immense rise of the Internet, attacks and malicious behaviors pose a huge threat to our computing environment. Brute-force attack is among the most prominent and commonly used attacks, achieved out using password-attack tools, a wordlist dictionary, and a usernames list—obtained through a so-called an enumeration attack. In this paper, we investigate username enumeration attack detection on SSH protocol by using machine-learning classifiers. We apply four asymmetrical classifiers on our generated dataset collected from a closed-environment network to build machine-learning-based models for attack detection. The use of several machine-learners offers a wider investigation spectrum of the classifiers’ ability in attack detection. Additionally, we investigate how beneficial it is to include or exclude network ports information as features-set in the process of learning. We evaluated and compared the performances of machine-learning models for both cases. The models used are k-nearest neighbor (K-NN), naïve Bayes (NB), random forest (RF) and decision tree (DT) with and without ports information. Our results show that machine-learning approaches to detect SSH username enumeration attacks were quite successful, with KNN having an accuracy of 99.93%, NB 95.70%, RF 99.92%, and DT 99.88%. Furthermore, the results improve when using ports information.
FakeAP Detector: An Android-Based Client-Side Application for Detecting Wi-Fi Hotspot Spoofing
(IEEE Access, 2022-01-27) Mwinuka, Lunodzo; Agghey, Abel; Kaijage, Shubi; Ndibwile, Jema
Network spoofing is becoming a common attack in wireless networks. The trend is going high due to an increase in Internet users. Similarly, there is a rapid growth of numbers in mobile devices in the working environments and on most official occasions. The trends pose a huge threat to users since they become the prime target of attackers. More unfortunately, mobile devices have weak security measures due to their limited computational powers. Current approaches to detect spoofing attacks focus on personal computers and rely on the network hosts’ capacity, leaving guest users with mobile devices at risk. Some approaches on Android-based devices demand root privilege, which is highly discouraged. This paper presents an Android-based client-side solution to detect the presence of fake access points in a perimeter using details collected from probe responses. Our approach considers the difference in security information and signal level of an access point (AP). We present the detection in three networks, (i) open networks, (ii) closed networks and (iii) networks with captive portals. As a departure from existing works, our solution does not require root access for detection, and it is developed for portability and better performance. Experimental results show that our approach can detect fake access points with an accuracy of 99% and 99.7% at an average of 24.64 and 7.78 milliseconds in open and closed networks, respectively.
Smart System for Controlling and Monitoring Water and Turbidity Levels in Dam Reservoir using Micro-Controller Technology
(Engineering, Technology & Applied Science Research, 2022-01) Iribagiza, Marie; Michael, Kisangiri; Ndibwile, Jema; Sebahire, Felicien
A micro-controller-based technology has been developed for monitoring and controlling the water quality and quantity in dam reservoirs by using various sensors. This system is able to automatically detect and measure the changes in water and turbidity levels of incoming water for hydropower production. In this project, an Arduino UNO micro-controller and GSM Technology control the operations of the system through sending messages and regulating automatic water valves according to the instant status of the dam water. The developed prototype has four units: sensing unit, processing unit, displaying unit, and alerting unit. In the sensing unit, the ultrasonic sensor continuously monitors the change in water levels and the turbidity sensor takes turbidity measurements of incoming water. In the processing unit, the detected data are collected and fed to the microcontroller for further processing. This technology is expected to reduce the time and cost incurred during the hydropower plant operations by using a small amount of manpower and will facilitate fast information collection.