DRC 2024
Permanent URI for this collectionhttp://repository.kln.ac.lk/handle/123456789/29875
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Item LEVERAGING LARGE LANGUAGE MODELS IN CYBERSECURITY: A SYSTEMATIC REVIEW OF EMERGING METHODS AND TECHNIQUES(The Library, University of Kelaniya, Sri Lanka., 2024) Sandaruwan, T.; Wijayanayake, J.; Senanayake, J.This systematic literature review examined how Large Language Models (LLMs) can be incorporated with vulnerability scanning and other cybersecurity tools and explored and assessed ways to improve cybersecurity practices. The PRISMA model was used, and the search was conducted using specific search terms in the leading databases such as the ACM Digital Library, IEEE Xplore Digital Library, and ScienceDirect from 2018 to July 2024. Initially, 313 records were gathered and reduced the count was reduced to 48 articles after applying the inclusion criteria. The findings were structured to answer the research questions regarding the approaches applied to incorporate LLMs with cybersecurity tools and the strengths and limitations of these tools based on the identified methodologies. The methods were reviewed and classified into Training and Adaptation Methods, Integration and Deployment Methods, and Inference and Utilization Techniques. After that, the accuracies of these methods were presented. The results show that fine-tuning and domain adaptation improves LLMs’ performance in cybersecurity tasks. In addition, fine-tuning, prompt engineering, and few-shot learning enhance models for specific tasks, making them more efficient in practical applications.Item IMPACT OF CLOUD ENTERPRISE SYSTEMS ON BUSINESS SECURITY AND BUSINESS CONTINUITY IN SMES IN SRI LANKA: A SYSTEMATIC LITERATURE REVIEW(The Library, University of Kelaniya, Sri Lanka., 2024) Malshan, W. P. P.; Wijayanayake, W. M. J. I.The adoption of cloud enterprise systems presents a transformative opportunity for small and medium enterprises (SMEs) in Sri Lanka, particularly in enhancing business security and continuity. This research investigates how these systems can effectively address critical challenges faced by SMEs, including cybersecurity threats, regulatory compliance, and infrastructural constraints. Utilizing a mixed-methods approach, the study integrates a systematic literature review with qualitative data from interviews and focus groups, as well as quantitative data from structured surveys. The findings reveal that while cloud technologies provide significant benefits in terms of data security, operational efficiency, and disaster recovery, the adoption process is hindered by unique local challenges. Key barriers identified include inadequate technological infrastructure, limited awareness among stakeholders, and regulatory hurdles that complicate implementation. To tackle these issues, the research proposes a tailored cybersecurity framework designed to offer practical guidelines for SMEs, enhancing their security posture. Moreover, strategic recommendations are presented to assist policymakers and technology providers in creating a supportive environment for cloud adoption. This research contributes to a deeper understanding of the role of cloud enterprise systems in improving business security and continuity for SMEs in Sri Lanka. It offers actionable insights for stakeholders aiming to cultivate a resilient and secure business ecosystem. By addressing the specific needs and challenges of SMEs, the study aims to promote a more robust adoption of cloud technologies, ultimately supporting the growth and sustainability of these enterprises in the evolving digital landscape. Overall, this research underscores the importance of cloud solutions in fostering a secure and efficient operational framework for SMEs in Sri Lanka.