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All Journal The Indonesian Journal of Computer Science
Tshilongamulenzhe, Tshimangadzo
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Computer Science & IT Electrical & Electronics Engineering Engineering

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Machine Learning-Based Security Algorithms for Detecting and Preventing DDoS Attacks on the IoT: State-of-the-Art, Challenges, and Future Directions Baloyi, Coster; Mathonsi, Topside; Du Plessis, Deon; Muchenje, Tonderai; Tshilongamulenzhe, Tshimangadzo
The Indonesian Journal of Computer Science Vol. 14 No. 3 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i3.4853

Abstract

Abstract - The Internet of Things (IoT) represents a vast network of interconnected devices equipped with software, sensors, and other technologies that enable data exchange and autonomous operation with other devices and systems without human intervention over the internet. IoT applications span across various sectors, including agriculture, education, healthcare, and communication. However, Distributed Denial of Service (DDoS) attacks continue to pose significant risks to the IoT network due to current challenges of classification efficiency and response times by the existing algorithms, such as Decision Tree (DT), Linear Regression (LR), and K-means. This paper provides a comprehensive review of DDoS attack types within the IoT networks. Secondly, the paper critically examines and analyses the challenges and opportunities inherent in leveraging Machine Learning (ML) algorithms for detecting, preventing, and mitigating these attacks. Finally, it presents the categories of IoT performance metrics, and their statistics found in the Literature over the Past decade.
A Model to Amplify Transmission Quality of Satellite Television Lebogang Maja; Deon du Plessis; Mathonsi, Topside; Tshilongamulenzhe, Tshimangadzo
The Indonesian Journal of Computer Science Vol. 14 No. 3 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i3.4861

Abstract

One of the various applications of communication satellite technologies is broadcasting satellite television (TV). In TV broadcasting, satellite communication is the easiest way to transmit many services and offers a variety of choices across a varied region, thereby overcoming the need for the complex infrastructure of terrestrial transmitters that a terrestrial network needs to broadcast its signals throughout a wide range area like countries or continents and providing quality digital TV viewing. However, Satellite TV broadcasting has a deficiency of outage effect caused by rain fade that instigate due to bad raining weather which at once will cuts signal transmission from the transmitter satellite to the receiver dish. this study was undertaken to explore the challenges that satellite TV broadcasting faces, which is caused by the rain fade effect. Thereafter, a model to amplify the transmission quality of satellite television is designed. The proposed Gau-satcomm algorithm, ITU-R model, and SAM model had an average BER of 5%, 8%, and 10%, respectively. Additionally, the Gau-Satcomm algorithm, SAM model, and ITU-R model experienced 4%, 9%, and 11% attenuation, respectively.  Furthermore, the study compared outage probability across three algorithms at frequencies over 10 GHz, the proposed Gau-satcomm algorithm, the ITU-R algorithm, and the SAM algorithm minimized outages by 10%, 7%, and 5%, respectively. Therefore, the proposed Gau-Satcomm outperforms these traditional algorithms in regard to average BER, a reduced average attenuation, and outage probability.
Enhanced Security Algorithm for Detecting Distributed Denial of Services Attacks in Cloud Computing Baloyi, Coster; Mathonsi, Topside E.; Plessis, Deon Du; Tshilongamulenzhe, Tshimangadzo
The Indonesian Journal of Computer Science Vol. 14 No. 4 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i4.4888

Abstract

Cloud Computing has the benefit of offering on-demand scalable services to its customers without having to invest much on hardware infrastructure, resources and software. Most private and public sectors are moving to the Cloud. As a result, Cloud Computing has become an ideal option due to its flexibility, scalability and cost efficiency. The existence of vulnerabilities in the network systems hosting Cloud have raised an opportunity for attackers to launch attacks in Cloud Computing. The intruders attack business applications such as webservers, financial servers, and other servers exploiting Distributed Denial of Service (DDoS) attacks. This paper proposed a Real-Time Network Traffic Attack Detection (RTNTAD) algorithm to detect DDoS attacks using real-time dataset to mitigate DDoS attacks. MATLAB was employed to evaluate the performance of RTNTAD. The proposed RTNTAD algorithm has achieved 99.2% detection rate, 99.5% classification of DDoS attacks, 0.9% connectivity time out and less than 18% false positive.
Co-Authors Baloyi, Coster Deon du Plessis Du Plessis, Deon Lebogang Maja Mathonsi, Topside Mathonsi, Topside E. Muchenje, Tonderai Plessis, Deon Du