Forthcoming and Online First Articles

International Journal of Critical Computer-Based Systems

International Journal of Critical Computer-Based Systems (IJCCBS)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Critical Computer-Based Systems (One paper in press)

Regular Issues

  • Enhancing IoMT Security: Spotted Hyena Optimised Bi-Layered Attention Adaptive Recurrent Network for Intrusion Detection   Order a copy of this article
    by Smiley Gandhi, Santosh Kumar, Poongodi T, Sampath Kumar K. 
    Abstract: Intrusion detection is essential to computer and network security because it detects unauthorised or malicious activity. It monitors and analyses network or system activity in real-time to alert or act on suspicious. Internet of Medical Things (IoMT) uses intrusion detection and attack detection systems to protect medical devices, healthcare systems, and patient data from cyberattacks. Researcher introduces a new IoMT-supported Spotted Hyena Optimized Bi-Layered Attention Adaptive Recurrent Network (SHO-BAARNN) for intrusion detection. The Spotted Hyena Optimization (SHO) is used to adjust model parameters for better robustness and efficiency when processing IoMT data. The adaptive recurrent network enables real-time intrusion detection, while the BAARNN structure offers dual attention techniques to selectively focus on important data aspects. The incorporation of optimisation, attention mechanisms, and recurrent networks, among other practical implications, makes it an effective tool for real-time detection of intrusions, providing improved security for sensitive healthcare data and medical equipment.
    Keywords: Intrusion detection; Internet of Medical Things (IoMT); Packet level features; Correlation-based feature selection; SHO-BAARNN.
    DOI: 10.1504/IJCCBS.2025.10072314
     

 

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