Forthcoming 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 Articles will not be published until the final proofs are validated by their authors.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 (3 papers 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
     
  • An analysis of secure software delivery validation using Blockchain   Order a copy of this article
    by Prabadevi Boopathy, Mayank Kumar, Malathy Batumalay 
    Abstract: Due to a lack of security in the supply chain of the software delivery process, the proposed method aims to address the challenges encountered during software delivery and mitigate the attack surface of software supply chain attacks. Blockchain technology establishes trust by verifying software packages and their developers, thereby achieving this goal, reducing the risk of executing malicious or compromised software. The proof of security is rooted in the immutable nature of blockchain. This feature provides a tamperproof record of software developers and the packages they publish, instilling a high level of trust in the verification process. The system holds the promise of a future where organisations can confidently verify the identity of software developers, allowing them to trust only the software from vendors they trust. When a tampered package enters the delivery process, the installation checks will promptly detect the compromise, leading to the failure of the attack chain.
    Keywords: Blockchain; software validation; identity; software delivery; supply chain.
    DOI: 10.1504/IJCCBS.2025.10074842
     
  • Identifying Security Vulnerabilities in Source Code with Safety Verification   Order a copy of this article
    by Salim Yahia Kissi, Rabéa Ameur Boulifa, Yassamine Seladji 
    Abstract: Ensuring the security of modern software systems is critical due to their increasing complexity and interconnectedness. Despite automated testing and bug-finding efforts, detecting security flaws remains challenging. Most research on software security issues primarily focuses on the source code of programs, neglecting the runtime environment and platforms. Such analyses may overlook problems that arise from the choice of execution machine, exposing them to the risk of missing more significant flaws and obscuring serious vulnerabilities. To address this gap, our approach detects security vulnerabilities, specifically errors in arithmetic operations in C/C++ programs, by analysing both source code and the execution environment. Central to our method is a knowledge base with precise logical formulas describing the impact of the execution environment on program behaviour. This article details how our knowledge base is built and expanded, and how our algorithm transforms vulnerability detection into a satisfiability problem, enabling the use of formal methods.
    Keywords: Formal Analysis; Vulnerabilities detection; Static analysis; Runtime environment specifications.
    DOI: 10.1504/IJCCBS.2025.10075749
     

 

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