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Articles

Vol. 2 No. 1 (2022): Cybersecurity and Network Defense Research (CNDR)

Vulnerability Assessment: Analyzing Automated Scanning Techniques for Vulnerability Assessment to Identify Weaknesses and Security Flaws in Network Infrastructure and Systems

Published
25-07-2024

Abstract

This research paper explores automated scanning techniques for vulnerability assessment, focusing on their role in identifying weaknesses and security flaws in network infrastructure and systems. The paper examines various automated scanning tools and methodologies, discussing their effectiveness, limitations, and best practices. The study aims to provide insights into the evolving landscape of vulnerability assessment, highlighting the importance of automated scanning in maintaining robust cybersecurity posture.

References

  1. References
  2. Pargaonkar, Shravan. "A Review of Software Quality Models: A Comprehensive Analysis." Journal of Science & Technology 1.1 (2020): 40-53.
  3. Raparthi, Mohan, Sarath Babu Dodda, and SriHari Maruthi. "Examining the use of Artificial Intelligence to Enhance Security Measures in Computer Hardware, including the Detection of Hardware-based Vulnerabilities and Attacks." European Economic Letters (EEL) 10.1 (2020).
  4. Pargaonkar, Shravan. "Bridging the Gap: Methodological Insights from Cognitive Science for Enhanced Requirement Gathering." Journal of Science & Technology 1.1 (2020): 61-66.
  5. Raparthi, Mohan, Sarath Babu Dodda, and Srihari Maruthi. "AI-Enhanced Imaging Analytics for Precision Diagnostics in Cardiovascular Health." European Economic Letters (EEL) 11.1 (2021).
  6. Pargaonkar, Shravan. "Future Directions and Concluding Remarks Navigating the Horizon of Software Quality Engineering." Journal of Science & Technology 1.1 (2020): 67-81.
  7. Vyas, Bhuman. "Ensuring Data Quality and Consistency in AI Systems through Kafka-Based Data Governance." Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal 10.1 (2021): 59-62.
  8. Pargaonkar, Shravan. "Quality and Metrics in Software Quality Engineering." Journal of Science & Technology 2.1 (2021): 62-69.
  9. Pargaonkar, Shravan. "The Crucial Role of Inspection in Software Quality Assurance." Journal of Science & Technology 2.1 (2021): 70-77.
  10. Vyas, Bhuman. "Optimizing Data Ingestion and Streaming for AI Workloads: A Kafka-Centric Approach." International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068 1.1 (2022): 66-70.
  11. Rajendran, Rajashree Manjulalayam. "Scalability and Distributed Computing in NET for Large-Scale AI Workloads." Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal 10.2 (2021): 136-141.
  12. Pargaonkar, Shravan. "Unveiling the Future: Cybernetic Dynamics in Quality Assurance and Testing for Software Development." Journal of Science & Technology 2.1 (2021): 78-84.
  13. Vyas, Bhuman. "Ethical Implications of Generative AI in Art and the Media." International Journal for Multidisciplinary Research (IJFMR), E-ISSN: 2582-2160.
  14. Rajendran, Rajashree Manjulalayam. "Exploring the Impact of ML NET (http://ml. net/) on Healthcare Predictive Analytics and Patient Care." Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal 11.1 (2022): 292-297.
  15. Pargaonkar, Shravan. "Unveiling the Challenges, A Comprehensive Review of Common Hurdles in Maintaining Software Quality." Journal of Science & Technology 2.1 (2021): 85-94.
  16. Pargaonkar, S. (2020). A Review of Software Quality Models: A Comprehensive Analysis. Journal of Science & Technology, 1(1), 40-53.
  17. Raparthi, M., Dodda, S. B., & Maruthi, S. (2020). Examining the use of Artificial Intelligence to Enhance Security Measures in Computer Hardware, including the Detection of Hardware-based Vulnerabilities and Attacks. European Economic Letters (EEL), 10(1).
  18. Pargaonkar, S. (2020). Bridging the Gap: Methodological Insights from Cognitive Science for Enhanced Requirement Gathering. Journal of Science & Technology, 1(1), 61-66.
  19. Raparthi, M., Dodda, S. B., & Maruthi, S. (2021). AI-Enhanced Imaging Analytics for Precision Diagnostics in Cardiovascular Health. European Economic Letters (EEL), 11(1).
  20. Vyas, B. (2021). Ensuring Data Quality and Consistency in AI Systems through Kafka-Based Data Governance. Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal, 10(1), 59-62.
  21. Rajendran, R. M. (2021). Scalability and Distributed Computing in NET for Large-Scale AI Workloads. Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal, 10(2), 136-141.
  22. Pargaonkar, S. (2020). Future Directions and Concluding Remarks Navigating the Horizon of Software Quality Engineering. Journal of Science & Technology, 1(1), 67-81.
  23. Vyas, B. (2022). Optimizing Data Ingestion and Streaming for AI Workloads: A Kafka-Centric Approach. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 1(1), 66-70.
  24. Pargaonkar, S. (2021). Quality and Metrics in Software Quality Engineering. Journal of Science & Technology, 2(1), 62-69.
  25. Vyas, B. Ethical Implications of Generative AI in Art and the Media. International Journal for Multidisciplinary Research (IJFMR), E-ISSN, 2582-2160.
  26. Rajendran, R. M. (2022). Exploring the Impact of ML NET (http://ml. net/) on Healthcare Predictive Analytics and Patient Care. Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal, 11(1), 292-297.
  27. Pargaonkar, S. (2021). The Crucial Role of Inspection in Software Quality Assurance. Journal of Science & Technology, 2(1), 70-77.
  28. Pargaonkar, S. (2021). Unveiling the Future: Cybernetic Dynamics in Quality Assurance and Testing for Software Development. Journal of Science & Technology, 2(1), 78-84.
  29. Pargaonkar, S. (2021). Unveiling the Challenges, A Comprehensive Review of Common Hurdles in Maintaining Software Quality. Journal of Science & Technology, 2(1), 85-94.