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Quarterly Journal of Emerging Technologies and Innovations

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Published

2022-01-07

Issue

Vol. 7 No. 1 (2022): QJETI-JANUARY-MARCH-2022

Section

Articles

How to Cite

Ahmed Fathy, Noha El-Sayed, & Khaled Salah. (2022). Enhancing System Reliability and Resilience through Advanced Anomaly Detection Techniques in Critical Infrastructures. Quarterly Journal of Emerging Technologies and Innovations, 7(1), 17–39. Retrieved from https://vectoral.org/index.php/QJETI/article/view/146

Enhancing System Reliability and Resilience through Advanced Anomaly Detection Techniques in Critical Infrastructures

Ahmed Fathy

Department of Computer Science, Suez Canal University

Noha El-Sayed

Department of Computer Science, Zagazig University

Khaled Salah

Department of Computer Science, South Valley University

Keywords: Python, TensorFlow, Scikit-learn, Anomaly Detection

Abstract

The research paper "Enhancing System Reliability with Anomaly Detection" explores the pivotal role of anomaly detection techniques in improving system reliability across various industries, including aerospace, healthcare, telecommunications, and automotive. System reliability, defined as the probability of a system performing its intended function without failure over a specified period, is quantified using metrics such as Mean Time Between Failures (MTBF) and Mean Time To Repair (MTTR). The paper highlights the challenges in maintaining system reliability due to the increasing complexity of systems, dynamic operational environments, and the limitations of traditional monitoring methods. Anomaly detection, which identifies patterns in data that deviate from expected behavior, is proposed as a solution to these challenges. The research investigates various anomaly detection methods, including statistical methods, machine learning algorithms, and deep learning techniques, assessing their effectiveness in different contexts. The study aims to identify the most effective methods for enhancing system reliability, offering practical recommendations for organizations. Through a comprehensive analysis of existing literature, methodology, and findings, the paper provides valuable insights into how early detection of anomalies can lead to proactive maintenance strategies, reduced downtime, and improved overall system performance.

Author Biographies

Ahmed Fathy, Department of Computer Science, Suez Canal University

 

 

 

Noha El-Sayed, Department of Computer Science, Zagazig University

 

 

 

Khaled Salah, Department of Computer Science, South Valley University

 

 

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Submission Guidelines for the Journal of Quarterly Journal of Emerging Technologies and Innovations (QJETI) General Guidelines:

  1. Article Types: We accept a variety of article types including Original Research Articles, Review Papers, Short Reports, and Opinion Pieces.

  2. Language: Manuscripts must be written in English, and should be clear, concise, and free of jargon.

  3. Length: There is no strict word limit, but Original Research Articles should generally be between 4,000 and 10,000 words, including references.

  4. Formatting: Manuscripts should be submitted as a single Word or LaTeX document, formatted in double-spaced 12-point font.

  5. Abstract: An abstract of 250-300 words is required for all submissions, summarizing the key objectives, methods, findings, and implications of the research.

Manuscript Structure:

  • Title Page: Must include the title, author names, affiliations, and contact information for the corresponding author.

  • Introduction: Provide background, state the problem, and outline objectives.

  • Methods: Detail the methods and tools used in your research.

  • Results: Present the findings of your study.

  • Discussion: Interpret results, discuss their impact, and suggest future research directions.

  • Conclusion: Summarize the main points of the paper.

  • References: Citations should be formatted according to the IEEE/APA style.

Ethical Guidelines:

Authors must ensure that their research adheres to ethical standards and that informed consent has been obtained for any human or animal subjects involved.

Plagiarism:

The Journal of Computational Social Dynamics uses plagiarism detection software. Any manuscript found to include plagiarized content will be rejected.

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All submissions undergo a double-blind peer review process. Authors can expect initial feedback within six to eight weeks.

Submission Process:
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  2. Submit your manuscript through our online portal.
  3. After submission, you will receive a confirmation email with a manuscript ID for tracking purposes.
Revisions:

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For any questions or concerns, please contact the editorial office at editorial@vectoral.org. Thank you for considering QJETI as a venue for your research.

Published by Vectoral Publishing, the Quarterly Journal of Emerging Technologies and Innovations maintains high standards in peer-review and scientific inquiry. Authors who wish to submit manuscripts should adhere to the guidelines detailed on our website, www.vectoral.org/QJETI. Vectoral Publishing does not bear any responsibility for the accuracy of information or for any outcomes related to the use of the research published. For editorial correspondence and submissions, please reach out to editorial@vectoral.org.

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