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 Articles will not be published until the final proofs are validated by their authors.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 (5 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, T. Poongodi, K. Sampath Kumar 
    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 optimised bi-layered attention adaptive recurrent network (SHO-BAARNN) for intrusion detection. The spotted hyena optimisation (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; spotted hyena optimised bi-layered attention adaptive recurrent network; SHO-BAARNN; real-time data streams.
    DOI: 10.1504/IJCCBS.2025.10072314
     
  • An analysis of secure software delivery validation using blockchain   Order a copy of this article
    by B. Prabadevi, 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 increasing complexity and interconnectedness. While automated testing and bug-finding tools have made progress, detecting security flaws - especially those related to runtime behaviour - remains a significant challenge. Existing research in software security has concentrated on source code analysis and often ignores how the execution environment affects program semantics, leaving machine-dependent vulnerabilities undetected. To bridge this gap, our approach analyses source code with awareness of its execution environment, acknowledging that many flaws arise from subtle mismatches between the two. Our work targets arithmetic errors in C/C+ + programs by modelling how the execution context shapes program behaviour. This article presents the construction of our knowledge base and explains how it integrates with our algorithm to enable accurate, environment-aware vulnerability detection using precise logical formulas, enabling the reformulation of vulnerability detection as a satisfiability problem suitable for automated reasoning using formal methods.
    Keywords: formal analysis; vulnerabilities detection; static analysis; runtime environment specifications.
    DOI: 10.1504/IJCCBS.2025.10075749
     
  • An enhanced test case prioritisation with cyber-security detection using CMSANN for banking or finance software   Order a copy of this article
    by Durga Praveen Deevi, Naga Sushma Allur, Koteswararao Dondapati, Himabindu Chetlapalli, Thinagaran Perumal 
    Abstract: In the software development process, software testing executes a program to detect errors. During this process, security attacks may occur, posing significant threats. Incorporating AI into cybersecurity testing processes can help organisations protect sensitive financial data from unauthorised access. So, this research methodology proposed a CMSANN-based cybersecurity prediction for software testing. Initially, the test cases are generated and prioritised using the WW-ArCa-PA approach in the banking or finance application. Then, it enters the data structuring phase. Data are mapped using AKNMHC and reduced using the HS approach in this phase. Then, the features are extracted and given to the cyber-security detection phase. The anomaly dataset is given as input, and pre-processing is performed using MVI, numeralisation, and normalisation. After pre-processing, the features are extracted, and then data are balanced using the ACA-CTSYN approach. The balanced data is given to the CMSANN classifier for cyber security detection.
    Keywords: artificial intelligence; AI; convolutional multi-head self-improving attention neural network; CMSANN; waterwheel Arnold's cat plant algorithm; WW-ArCa-PA; agglomerative kernel normalised Mahalanobis hierarchical clustering; AKNMHC; adaptive cover tree synthetic sampling; ADA-CTSYN; cyber security and software testing.
    DOI: 10.1504/IJCCBS.2025.10077285
     
  • Phishing attack detection and zero trust-based verification for secure data transfer using BTEL-GRU   Order a copy of this article
    by Rajya Lakshmi Gudivaka, Basava Ramanjaneyulu Gudivaka, Raj Kumar Gudivaka, Dinesh Kumar Reddy Basani, Sri Harsha Grandhi, M.M. Kamruzzaman 
    Abstract: The authentication and access control of the user's data using zero trust architecture (ZTA) is necessary to prevent data breaches. Initially, the user registers in the cloud, and here, the hashcode is generated using the substitution cipher-based whirlpool hashing algorithm (SC-WHA). In the phishing attack detection model, word embedding is done using Kaiming normalised Xavier-based bidirectional encoder representations from Transformers (KNX-BERT) for content extracted from the email dataset, the features are extracted, and the dimensionality is reduced using linear discriminant analysis (LDA). The word embedded and reduced features are classified using Bernoulli-dropout TanhExp logish gated recurrent unit (BTEL-GRU). During testing, the attacked data is blocked, and the non-attacked data is secured using deltoid spiral curve cryptography (DS-CC) and uploaded to the cloud. Hence, in the proposed model, the phishing attack is identified with an accuracy of 98.77586945%, and the multifactor hashcode verification is done with a hashcode generation time of 1,326 ms for secured data transfer.
    Keywords: zero trust architecture; phishing attack detection; PAD; decentralised user management; data security; whirlpool hashing algorithm; WHA; mobile security system; gated recurrent unit; GRU.
    DOI: 10.1504/IJCCBS.2026.10077743