Review of AI driven Intrusion Detection System on Network based attacks

Approved

Relevance and Originality

The research article presents a timely and relevant examination of the integration of Artificial Intelligence (AI) in Intrusion Detection Systems (IDS). By addressing the evolving landscape of cybersecurity and highlighting the advancements in AI, the paper contributes to ongoing discussions in the field. The originality lies in its comparative analysis of traditional and advanced AI techniques, which offers valuable insights into how these innovations enhance the effectiveness and efficiency of IDS. This unique perspective not only fills existing gaps in the literature but also sets the stage for future research in AI-driven cybersecurity solutions.

Methodology

The methodology section of the research article effectively outlines the approaches used to analyze the integration of AI in IDS. It provides a clear framework for understanding the evolution of IDS, emphasizing both traditional methods and contemporary AI techniques, including machine learning and deep learning. However, the article could be strengthened by offering more detailed explanations of the specific methods employed in the analysis. Including information on data sources, evaluation metrics, and any experimental designs would provide greater transparency and allow for a better assessment of the findings.

Validity & Reliability

The validity and reliability of the findings are somewhat supported by the comprehensive nature of the analysis, which includes a comparison of various AI methodologies in IDS. Nonetheless, the article should incorporate more empirical evidence to enhance its claims. Providing case studies or examples of successful implementations of AI in IDS would bolster the credibility of the assertions made. Additionally, discussing any limitations in the reviewed studies would offer a more balanced view, reinforcing the article's reliability in drawing conclusions about AI's role in improving IDS.

Clarity and Structure

The research article is well-structured and presents its arguments in a logical sequence, making it accessible to readers with varying levels of expertise in cybersecurity. The organization facilitates a clear understanding of the evolution of IDS and the transformative role of AI. However, the clarity could be improved by defining key concepts and terminology early in the paper. Additionally, incorporating visual aids, such as diagrams or tables, would enhance comprehension and help summarize complex information effectively.

Result Analysis

The result analysis in the research article provides insightful comparisons of traditional and AI-based IDS techniques, focusing on their strengths and weaknesses. However, the article would benefit from a more in-depth exploration of the implications of these findings in real-world applications. Discussing specific examples where AI has significantly improved IDS performance would add depth to the analysis. Furthermore, the article should address the potential challenges and limitations faced in implementing AI technologies in IDS, thereby offering a more comprehensive overview of the future landscape of cybersecurity.