http://dlib.iit.ac.lk/xmlui/handle/123456789/1620 2026-04-08T18:21:36Z 2026-04-08T18:21:36Z Anggapulige, Panitha http://dlib.iit.ac.lk/xmlui/handle/123456789/2174 2024-06-03T04:17:23Z 2023-01-01T00:00:00Z

DDoS Attack Mitigation in Content Delivery Networks using Blockchain and Machine Learning Anggapulige, Panitha "Distributer Denial of Services attacks remain a persistent and severe threats to internet and internet infrastructure and services, causing significant financial losses and disrupting critical online operations. This these address the escalating challenges of combating DDoS attacks that against the content delivery networks by proposing and innovative conceptual framework that integrates with serval technologies like Machine learning, blockchain. The first part of the research focuses on developing a framework for ML-based DDoS detection system capable of identifying and mitigating attack traffic in real-time. Using machine learning built in solution analysis and dataset analysis, a feature-rich model is proposed to recognize attack patterns, thereby enabling early identification and timely response to evolve attack techniques. The second part of the thesis introduces a novel Blockchain-based reputation system, which use for a secure and decentralized environment for communication and cooperation between CDN nodes. By leveraging the transparency and immutability of Blockchain, the proposed reputation system ensures the trustworthiness and accountability of CDN nodes, promoting collaboration to handle DDoS attacks more effectively. The final segment explores the integration of Content Delivery Networks with the ML-based detection and the Blockchain reputation system. This integration empowers CDNs to distribute network traffic efficiently, optimize resource allocation, and proactively defend against DDoS attacks across distributed server locations. Therefore, the proposed conceptual framework not only bolsters network performance but also enhances DDoS resilience by quickly diverting and filtering malicious traffic at the network's edge. To evaluate the effectiveness of the proposed conceptual framework, Self-evaluation and expert evaluation has done. The results demonstrate significant improvements in attack detection effectiveness, architecture and overall network robustness. In conclusion, this thesis contributes to the ongoing efforts to combat DDoS attacks by providing an innovative approach that leverages the potential of Machine Learning, Blockchain technology, and Content Delivery Networks. The integrated framework offers a comprehensive and powerful solution to mitigate DDoS attacks, safeguard network infrastructure, and preserve the uninterrupted functionality of critical online services."

2023-01-01T00:00:00Z Mohamed Amaan, Ahamed Ausaff http://dlib.iit.ac.lk/xmlui/handle/123456789/2173 2024-06-03T04:14:53Z 2023-01-01T00:00:00Z

Improving Current Cyber Security Awareness and Training Delivery a Conceptual Framework Mohamed Amaan, Ahamed Ausaff "With the recent pandemic more people are either working from home or working in a hybrid model and are exposed to newer cyber risk than before requiring these employees to receive security awareness training. However, the current security awareness landscape is found to be lacking due to factors such as rise in social engineering attacks, lack of engagement in the training material provided, organisations being more focused on achieving compliance to certain industry standards, and attention not being paid to emerging threats from AI. This research intends to develop a conceptual framework that plans to address the short coming of the current security awareness training landscape by proposing a framework that can personalize the security awareness training to the individual employees’ requirements leading to a more effective training outcome."

2023-01-01T00:00:00Z Peiris, Sulakkya http://dlib.iit.ac.lk/xmlui/handle/123456789/2172 2024-06-03T04:06:47Z 2023-01-01T00:00:00Z

A Lightweight Security Framework for the Internet of Things: Home Automation Peiris, Sulakkya "The escalating adoption of Internet of Things (IoT) devices has necessitated robust data encryption methods to safeguard sensitive information. An essential component of encryption is generating white noise to provide a reliable source of randomness. However, the challenge lies in developing lightweight white noise generation techniques suitable for resource constrained IoT devices, where computational efficiency and energy consumption are critical concerns. White noise serves as a fundamental building block for cryptographic algorithms, including key generation, initialization vectors, and one-time pads. However, the challenge lies in developing lightweight white noise generation techniques suitable for resource constrained IoT devices, where computational efficiency and energy consumption are critical concerns. Traditional cryptographic methods may be computationally heavy and impractical for the limited processing power and memory of IoT devices. Moreover, energy-efficient white noise generation is imperative to extend the battery life of battery-powered IoT devices, enhancing their overall operational lifespan and reducing maintenance costs. To address this, we leverage pseudorandom number generators (PRNGs), aiming to strike a balance between cryptographic strength and resource utilization. Finally, we will evaluate the effectiveness of the proposed IoT security framework. Ultimately, our research aims to contribute to the advancement of secure IoT applications, safeguarding sensitive data in the interconnected world of tomorrow."

2023-01-01T00:00:00Z Appuhamy, Hewayakge http://dlib.iit.ac.lk/xmlui/handle/123456789/2171 2024-06-03T04:03:40Z 2023-01-01T00:00:00Z

Technical Cybersecurity Readiness Framework for the Higher Educational Virtual Learning Environment in Sri Lanka Appuhamy, Hewayakge "The increasing reliance on virtual learning environments in higher education calls for robust cyber security measures to safeguard sensitive data, ensure uninterrupted learning experiences, and protect against cyber threats. This research study aims to develop a Technical Cyber Security Readiness Framework tailored to the higher educational virtual learning environment in Sri Lanka. The research begins with a comprehensive literature review, examining existing frameworks and best practices in cyber security for virtual learning environments globally. Drawing upon this knowledge, the research develops a framework specifically designed to address the unique challenges and requirements of the Sri Lankan higher educational context. The framework encompasses various aspects of cyber security. It provides a structured approach for institutions to assess their cyber security readiness and implement necessary measures to mitigate risks. An initial evaluation of the framework is conducted, assessing its effectiveness and applicability. Surveys, interviews, and technical assessments are employed to gauge the readiness of higher educational institutions in Sri Lanka. The evaluation identifies areas for improvement, such as enhancing awareness and understanding, strengthening security measures implementation, improving incident response capability, and upgrading infrastructure and technology. To address these improvements within the Minimum Viable Product (MVP) timeline, the research outlines specific steps, including collaboration with stakeholders, developing action plans, allocating resources, monitoring progress, and maintaining clear communication channels."

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