Review of AI driven Intrusion Detection System on Network based attacks

Not Approved

Relevance and Originality:

This review paper addresses a highly relevant topic in the field of cybersecurity—the integration of Artificial Intelligence (AI) in Intrusion Detection Systems (IDS). As cyber threats continue to evolve, enhancing IDS with AI is crucial for improving detection capabilities and response times. The originality of this research lies in its comprehensive exploration of the evolution of IDS from traditional methods to AI-driven approaches. By assessing the transformative impact of AI in this domain, the paper provides valuable insights that contribute to both academic and practical discussions on cybersecurity defenses.

Methodology:

The methodology of the paper is primarily a literature review, focusing on the evolution and comparison of different IDS techniques, including traditional methods and AI-based systems. The assessment of strengths and weaknesses across various contexts provides a nuanced understanding of the effectiveness of these approaches. However, the paper would benefit from clearer criteria for the selection of studies included in the review, as well as a more systematic approach to categorizing the methodologies discussed. Including specific case studies or examples of successful AI integration in IDS would also strengthen the research's empirical grounding.

Validity & Reliability:

The findings presented in the review appear valid, particularly given the comprehensive nature of the literature analyzed. By addressing both the strengths and weaknesses of traditional and AI-based IDS, the paper offers a balanced perspective that enhances its credibility. To bolster reliability, the paper could incorporate quantitative data or performance metrics demonstrating the effectiveness of AI-enhanced IDS in real-world scenarios. Additionally, a discussion on the challenges of implementing AI in IDS, such as data privacy concerns or the potential for false positives, would provide a more holistic view of the topic.

Clarity and Structure:

The article is well-structured, with a clear progression from the introduction of the topic to a detailed examination of different IDS techniques. The clarity of the writing effectively conveys complex concepts related to AI and cybersecurity, making the material accessible to a broad audience. However, some sections could benefit from more succinct explanations to avoid overwhelming readers with technical details. A clearer delineation of the various AI methodologies and their specific applications in IDS would improve overall readability and facilitate a better understanding of the content.

Result Analysis:

The result analysis effectively highlights the transformative impact of AI on IDS and provides insightful comparisons between traditional and advanced techniques. By discussing the potential of AI to enhance the effectiveness and efficiency of cybersecurity defenses, the paper contributes significantly to the field. However, the analysis could be deepened by including empirical evidence or case studies that demonstrate the practical benefits of AI integration in IDS. Additionally, outlining specific future research directions or potential challenges in the implementation of AI in IDS would enrich the discussion and offer a roadmap for further exploration in this critical area of cybersecurity.