JCSOpen Access

Journal of Cyber Security

ISSN:2579-0072(print)
ISSN:2579-0064(online)
Publication Frequency:Continuously

  • Online
    Articles

    72

  • on board
    editors

    20


About the Journal

Cybersecurity is the basis of information dissemination in the internet age.The Journal of Cyber Security focuses on all aspects of sciences, technologies, and applications relating to hardware security, software security and system security.

Indexing and Abstracting



Starting from July 2023, Journal of Cyber Security will transition to a continuous publication model, accepted articles will be promptly published online upon completion of the peer review and production processes.

  • Open Access

    ARTICLE

    A Comparative Performance Analysis of Machine Learning Models for Intrusion Detection Classification

    Journal of Cyber Security, Vol.6, pp. 1-23, 2024, DOI:10.32604/jcs.2023.046915
    Abstract The importance of cybersecurity in contemporary society cannot be inflated, given the substantial impact of networks on various aspects of daily life. Traditional cybersecurity measures, such as anti-virus software and firewalls, safeguard networks against potential threats. In network security, using Intrusion Detection Systems (IDSs) is vital for effectively monitoring the various software and hardware components inside a given network. However, they may encounter difficulties when it comes to detecting solitary attacks. Machine Learning (ML) models are implemented in intrusion detection widely because of the high accuracy. The present work aims to assess the performance of More >

  • Open Access

    ARTICLE

    Sentence Level Analysis Model for Phishing Detection Using KNN

    Journal of Cyber Security, Vol.6, pp. 25-39, 2024, DOI:10.32604/jcs.2023.045859
    Abstract Phishing emails have experienced a rapid surge in cyber threats globally, especially following the emergence of the COVID-19 pandemic. This form of attack has led to substantial financial losses for numerous organizations. Although various models have been constructed to differentiate legitimate emails from phishing attempts, attackers continuously employ novel strategies to manipulate their targets into falling victim to their schemes. This form of attack has led to substantial financial losses for numerous organizations. While efforts are ongoing to create phishing detection models, their current level of accuracy and speed in identifying phishing emails is less… More >

  • Open Access

    ARTICLE

    An Intrusion Detection Method Based on a Universal Gravitation Clustering Algorithm

    Journal of Cyber Security, Vol.6, pp. 41-68, 2024, DOI:10.32604/jcs.2024.049658
    Abstract With the rapid advancement of the Internet, network attack methods are constantly evolving and adapting. To better identify the network attack behavior, a universal gravitation clustering algorithm was proposed by analyzing the dissimilarities and similarities of the clustering algorithms. First, the algorithm designated the cluster set as vacant, with the introduction of a new object. Subsequently, a new cluster based on the given object was constructed. The dissimilarities between it and each existing cluster were calculated using a defined difference measure. The minimum dissimilarity was selected. Through comparing the proposed algorithm with the traditional Back More >

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