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    Transparent Peer Review By Scholar9

    "Advances in Intrusion Detection Systems: A Comprehensive Review of Emerging Techniques and Challenges in Cybersecurity Defence"

    Abstract

    The escalating threats from unauthorized activities in networks are met effectively by Intrusion Detection Systems (IDS), forming a key aspect of current cybersecurity. Inefficiencies of standard firewalls in catching sophisticated threats compel IDS to perpetually watch network traffic and system events for signs of malicious actions. IDS evolved in the 1980s due to the foundational work by Dorothy Denning. A variety of IDS solutions has appeared in recent years; from laboratory prototypes to market goods they conquer unauthorized access and potential security infractions via unique detection strategies. An IDS serves primarily to tell real attacks apart from normal processes and diminish the frequency of false positives that can strain security operators. Analysis of attack behaviours alongside their associated signatures helps IDS react quickly to possible risk and boosts an organization's security framework. The systems utilize two main detection techniques: Detection methods include tracking known attack signatures while anomaly-based techniques create normal profiles to spot anomalies that might mark an attack. This combined method enables companies to identify recognized and novel dangers efficiently. With their strength IDS contend with several issues like the dynamic techniques unauthorized users deploy to escape detection and the basic limitations associated with existing training data. As attacks use more sophisticated evasion techniques the necessity for ongoing upgrades to IDS technology is essential. Future investigations will emphasize the adoption of smart machine learning algorithms to improve how well systems detect risks and reduce erroneous signals.

    Reviewer Photo

    Priyank Mohan Reviewer

    badge Review Request Accepted
    Reviewer Photo

    Priyank Mohan Reviewer

    15 Oct 2024 12:41 PM

    badge Approved

    Relevance and Originality

    Methodology

    Validity & Reliability

    Clarity and Structure

    Results and Analysis

    Relevance and Originality

    The article addresses a pressing issue in cybersecurity: the need for effective Intrusion Detection Systems (IDS) in the face of increasingly sophisticated cyber threats. The relevance of this research is underscored by the growing reliance on digital infrastructure, which has made organizations more vulnerable to unauthorized activities. The discussion on the evolution of IDS, particularly its origins linked to the work of Dorothy Denning, adds a historical perspective that enhances the originality of the research. By analyzing the latest developments in IDS technology and their implications for cybersecurity, the article contributes valuable insights to the field.


    Methodology

    The article does not provide a detailed methodology section, which limits the reader's understanding of how the various IDS solutions were evaluated. A comprehensive review of the different types of IDS (e.g., network-based vs. host-based, signature-based vs. anomaly-based) could improve the discussion. Additionally, the article would benefit from the inclusion of specific case studies or examples that illustrate the effectiveness of various IDS implementations. A clear outline of the criteria used to assess the effectiveness of IDS solutions would also strengthen the methodological rigor of the research.


    Validity & Reliability

    The validity of the article's claims is supported by the recognition of the challenges posed by sophisticated cyber threats and the limitations of traditional firewalls. However, the article would be strengthened by referencing empirical studies or statistical data that demonstrate the efficacy of IDS in real-world applications. Discussing the challenges faced by IDS, such as false positives and the need for continuous updates, adds depth to the analysis but could be further supported with case studies or examples of IDS failures or successes in practice. Additionally, addressing the limitations of the existing training data used for IDS would improve the reliability of the findings.


    Clarity and Structure

    The article is well-structured, with a logical flow that guides the reader through the evolution of IDS and its significance in cybersecurity. However, the use of headings and subheadings to delineate different sections (such as the historical background, current technologies, and future directions) would enhance readability and organization. While the language is generally clear, some technical jargon could be simplified or explained to make the content more accessible to a broader audience. Providing definitions for terms like "false positives" and "attack signatures" would help readers unfamiliar with cybersecurity concepts.


    Result Analysis

    The article effectively highlights the strengths and challenges of IDS in detecting unauthorized activities. However, it would benefit from a more detailed discussion of the results associated with implementing IDS solutions. For example, including statistics on detection rates, false positive rates, or case studies illustrating the impact of IDS on organizational security would provide practical insights. Additionally, discussing the implications of emerging machine learning algorithms for enhancing IDS capabilities would further enrich the analysis. While the article identifies key issues and future directions for IDS technology, a more comprehensive exploration of these aspects would provide a deeper understanding of their importance in the evolving landscape of cybersecurity.

    Publisher Logo

    IJ Publication Publisher

    thankyou sir

    Publisher

    IJ Publication

    IJ Publication

    Reviewer

    Priyank

    Priyank Mohan

    More Detail

    Category Icon

    Paper Category

    Computer Engineering

    Journal Icon

    Journal Name

    IJNTI - INTERNATIONAL JOURNAL OF NOVEL TRENDS AND INNOVATION External Link

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    p-ISSN

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    e-ISSN

    2984-908X

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