Forthcoming and Online First Articles

International Journal of Critical Computer-Based Systems

International Journal of Critical Computer-Based Systems (IJCCBS)

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International Journal of Critical Computer-Based Systems (6 papers in press)

Regular Issues

  • A Deterministic Approach with Markov Chain Algorithm to Impose Higher Order Security in Dynamic Wireless Sensor Networks (DWSN)   Order a copy of this article
    by M. S. S. Sasikumar, Narayanan A.E 
    Abstract: Wireless sensor networks are deployed based on their application environment. Since WSN are modality based, they sense data based on the type of data, they must sense. Unless otherwise we deploy proper algorithms and governance on to the sensor nodes, they behave in a normal way. We tried an attempt to provide a pilot scheme to establish a scheme called ORDER optimal retrospective decision enrichment for reliability, which analyses the previous tasks of the sensor nodes and categorise those nodes under different categories related to specific tasks. The algorithm ORDER analyses the tasks and assigns the tasks to the sensor nodes and monitor whether the tasks are being performed in a time bound manner without any compromise into security aspects. Our model is compared with the existing benchmarked approaches and found better in terms of reliability, data integrity and data consistency, throughput and BER.
    Keywords: ORDER; Markov chain; deterministic; retrospective; sensor nodes; reliability; FEDSEC; adversarial; security; federated learning.
    DOI: 10.1504/IJCCBS.2024.10058153
  • Algorithm-Based Fault-Tolerant Parallel Sorting   Order a copy of this article
    by Edson T. Camargo, Elias Duarte 
    Abstract: High performance computing (HPC) systems often require substantial resources, and can take up to several hours or days to execute. Upon a failure, it is important to loose as little computation as possible. In this work we present an algorithm-based fault tolerance (ABFT) strategy for hypercube-based parallel algorithms. The strategy assumes the virtual VCube topology, which has several logarithmic properties that are preserved even as nodes fail. The strategy guarantees that the algorithm does not halt even after up to (N 1) nodes crash, in a system of N nodes. We use parallel sorting as a case study, describing how to make a fault-tolerant version of three parallel sorting algorithms: HyperQuickSort, QuickMerge and Bitonic Sort. The algorithms were implemented in MPI using ULMF to handle faults. Experimental results are presented showing the performance and robustness of the solution for sorting up to a billion integers in scenarios with faults.
    Keywords: High Performance Computing; Algorithm-Based Fault Tolerance; ULFM; Fault Tolerance.
    DOI: 10.1504/IJCCBS.2024.10060352
  • Application of Multi-Criteria Decision-Making Approach Using TOPSIS to identify the Vulnerable Time Zone of Earthquake Time Series Signal   Order a copy of this article
    by Prasenjit Das, Debabrata Datta, Suman Rajest George, Maria Michael Visuwasam L, Anuradha Thakare, J. Cypto 
    Abstract: Conventional analysis of time series signals representing earthquakes does not provide any clue about the vulnerability of such disastrous events. Time series signals contain P and S waves, which can detect earthquake epicentres. Due to the failure of the old method for determining earthquake susceptibility over time, decision-making is needed. This research suggests a multi-criteria decision-making method to determine earthquake signal risk time zones. This study used TOPSIS for this job. TOPSIS ranks greatest and worst resemblance to positive and negative ideal solutions. Alternatives and criteria constitute the decision matrix. Segmenting the earthquake's duration creates alternate time zones, and seismic signal dynamics are used to set criteria. Statistical mean and standard deviation are two criteria among many. Other criteria include Hurst exponent, power spectrum maximum amplitude, and segmented signal anomaly (assumed as alternate). The proposed approach was tested using Indian Meteorological Department Bhuj earthquake data. The paper describes how to evaluate criteria for a time zone alternative. To simplify computation, earthquake incidence is separated into 14 equal-length time segments. Results demonstrate that the proposed method accurately detects earthquake time series signal sensitive time zones.
    Keywords: earthquake time series; hurst exponent; multi-criteria decision-making approach; technique for order of preference by similarity to ideal solution; TOPSIS; vulnerable time zone.
    DOI: 10.1504/IJCCBS.2024.10062160
  • Refining Malware Detection with Enhanced Machine Learning Algorithms using Hyperparameter Tuning   Order a copy of this article
    by El Mouhtadi Walid, Mohamed E.L. Bakkali, Yassine Maleh, Soufyane Mounir, Karim Ouazzane 
    Abstract: The aim of this research is to investigate and demonstrate the advantages and limitations of various machine learning techniques for malware classification, specifically focusing on portable executable (PE) files. The study addresses common challenges in machine learning, such as overfitting and underfitting, by employing ensemble methods and pre-processing techniques, including feature selection and hyperparameter tuning. The primary objective is to enhance classifier performance in distinguishing between malicious and benign PE files. Through a comparative analysis of machine learning methodologies such as random forests, decision trees, and gradient boosting, the study highlights the superiority of the random forests algorithm, achieving an impressive accuracy rate of 99%. By thoroughly evaluating the strengths and limitations of each algorithm, the research provides valuable insights into effectively handling diverse malware categories. This paper underscores the significance of ensemble methods, feature engineering, and pre-processing in improving classifier performance for malware classification, specifically in the context of portable executable files.
    Keywords: Malware Detection; Machine Learning; Optimization; Hyperparameter Tunning; Data Balancing; Feature Selection.
    DOI: 10.1504/IJCCBS.2024.10062989
  • Highly Available Virtual Network Functions and Services Based on Checkpointing/Restore   Order a copy of this article
    by Giovanni Venancio, Elias Duarte 
    Abstract: Network Function Virtualization (NFV) technology has the potential to have a deep impact on how networks are built and managed. However, in order to achieve its full potential, it is necessary to guarantee the required dependability, and in particular the availability of VNFs (Virtualized Network Functions) and SFCs (Service Function Chains). This work presents NHAM: NFV High Availability Module for the NFV-MANO (NFV Management and Orchestration) reference model. NHAM allows the creation and management of highly-available virtual network services consisting of both stateless and stateful VNFs and SFCs. The architecture provides multiple recovery mechanisms that differ in terms of cost and latency. The solution does not require any modifications of the source code of VNFs/SFCs to make them highly-available. The strategy is based on VNF checkpoint/restore together with SFC buffer management. A prototype was implemented and experimental results are presented showing that carrier grade availability levels can be achieved.
    Keywords: Network Function Virtualization; Virtualized Network Functions; High Availability; Fault Tolerance.
    DOI: 10.1504/IJCCBS.2024.10062996
  • Using the Theorem of Inaccessibility to Assess Dependable Real-Time Networks   Order a copy of this article
    by Jeferson Souza, Frank Siqueira 
    Abstract: This paper builds on the foundations of computer-based networks in order to assess their dependable and real-time properties. We extend the analysis and modelling of network inaccessibility by using its associated theorem to gauge the origins of dependability issues during the network operation. We show how network transmissions in the presence of errors can be observed and analysed, implying a richer view and understanding of their negative impact to the whole distributed real-time ecosystem. We conclude, based on results obtained from performed simulations, that such a richer view opens room for more resilient computer-based networks, which contributes to an improved modelling and prototyping of distributed real-time systems running on top of them.
    Keywords: Dependability; Mixed-Critical; Network Errors; Real-time; Real-Time Assessment;Resilience.
    DOI: 10.1504/IJCCBS.2024.10063642