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AI-Driven Cybersecurity Frameworks for DevSecOps in Cloud-Based Healthcare APIs

Dr. T Murali Krishna

Associate Professor & HOD, Department of CSE, Ashoka Women's Engineering College, Kurnool, Andhra Pradesh, India

Abstract

The rapid digitization of healthcare systems and the adoption of cloud-native architectures have transformed how medical data is stored, processed, and exchanged. Cloud-based healthcare APIs, particularly those aligned with interoperability standards such as Health Level Seven International’s FHIR (Fast Healthcare Interoperability Resources), enable seamless integration among hospitals, insurers, telemedicine platforms, and third-party applications. However, this interconnected ecosystem introduces significant cybersecurity risks, including API abuse, ransomware, insider threats, and AI-driven cyberattacks. DevSecOps practices aim to embed security throughout the software development lifecycle, yet traditional rule-based defenses often fail to address evolving threat landscapes.

This paper proposes an AI-driven cybersecurity framework tailored for DevSecOps in cloud-based healthcare APIs. The framework integrates machine learning-based anomaly detection, automated threat intelligence, behavioral analytics, zero-trust architectures, and continuous compliance monitoring within CI/CD pipelines. By leveraging predictive analytics and real-time monitoring, the framework enhances early threat detection, reduces response time, and strengthens regulatory compliance with healthcare data protection laws. The research explores architecture design, integration strategies, implementation methodology, benefits, and limitations. The study concludes that AI-enhanced DevSecOps significantly improves resilience, scalability, and proactive defense capabilities in modern healthcare API ecosystems.

Article Information

Journal

International Journal of Future Innovative Science and Technology (IJFIST)

Volume (Issue)

Vol. 5 No. 5 (2022): International Journal of Future Innovative Science and Technology (IJFIST)

DOI

https://doi.org/10.15662/IJFIST.2022.0505003

Pages

9197-9206

Published

October 7, 2022
Copyright

Open Access

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Dr. T Murali Krishna (2022). AI-Driven Cybersecurity Frameworks for DevSecOps in Cloud-Based Healthcare APIs. International Journal of Future Innovative Science and Technology (IJFIST) , Vol. 5 No. 5 (2022): International Journal of Future Innovative Science and Technology (IJFIST) , pp. 9197-9206. https://doi.org/10.15662/IJFIST.2022.0505003

References

1. Sudhan, S. K. H. H., & Kumar, S. S. (2015). An innovative proposal for secure cloud authentication using encrypted biometric authentication scheme. Indian Journal of Science and Technology, 8(35), 1–5.
2. Gangina, P. (2022). Resilience engineering principles for distributed cloud-native applications under chaos. International Journal of Computer Technology and Electronics Communication, 5(5), 5760–5770.
3. Genne, S. (2022). Designing accessibility-first enterprise web platforms at scale. International Journal of Research and Applied Innovations (IJRAI), 5(5), 7679–7690.
4. Pujari, S. D., & Anusha, K. (2022). Effective prediction of autism using ensemble method. In Artificial Intelligence for Innovative Healthcare Informatics (pp. 103–115). Springer.
5. Ananth, S., Radha, D. K., Prema, D. S., & Nirajan, K. (2019). Fake news detection using convolution neural network in deep learning. International Journal of Innovative Research in Computer and Communication Engineering, 7(1), 49–63.
6. Chennamsetty, C. S. (2022). Hardware-software co-design for sparse and long-context AI models: Architectural strategies and platforms. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 5(5), 7121–7133.
7. Mudunuri, P. R. (2022). Automating compliance in biomedical DevOps: A policy-as-code approach. International Journal of Research and Applied Innovations (IJRAI), 5(2), 6770–6783.
8. Jaikrishna, G., & Rajendran, S. (2020). Cost-effective privacy preserving of intermediate data using group search optimisation algorithm. International Journal of Business Information Systems, 35(2), 132–151.
9. Anumula, S. R. (2022). Governance frameworks for automated enterprise decision systems. International Journal of Humanities and Information Technology (IJHIT), 4(1–3), 137–157.
10. Rajurkar, P. (2021). Deep learning models for predicting effluent quality under variable industrial load conditions. International Journal of Research and Applied Innovations, 4(5), 5826–5832.
11. Navandar, P. (2022). Enhancing cybersecurity in the digital age: Challenges and strategies. Journal of Artificial Intelligence & Cloud Computing.
12. Ponugoti, M. (2022). Integrating API-first architecture with experience-centric design for seamless insurance platform modernization. International Journal of Humanities and Information Technology (IJHIT), 4(1–3), 117–136.
13. Singh, A. (2020). Impact of network topology changes on performance. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 3(4), 3687–3692.
14. Sudhan, S. K. H. H., & Kumar, S. S. (2016). Gallant use of cloud by a novel framework of encrypted biometric authentication and multi level data protection. Indian Journal of Science and Technology, 9, 44.
15. Ramidi, M. (2022). Developing resilient offline-first architectures for mobile health and clinical research applications. International Journal of Computer Technology and Electronics Communication (IJCTEC), 5(1), 4518–4529.
16. Vimal Raja, G. (2022). Leveraging machine learning for real-time short-term snowfall forecasting using multisource atmospheric and terrain data integration. International Journal of Multidisciplinary Research in Science, Engineering and Technology, 5(8), 1336–1339.
17. Panda, M. R., & Kondisetty, K. (2022). Predictive fraud detection in digital payments using ensemble learning. American Journal of Data Science and Artificial Intelligence Innovations, 2, 673–707.
18. Anand, L., & Neelanarayanan, V. (2019). Feature selection for liver disease using particle swarm optimization algorithm. International Journal of Recent Technology and Engineering (IJRTE), 8(3), 6434–6439.
19. Sriramoju, S. (2022). Automated migration frameworks for legacy systems: A security-driven approach. International Journal of Computer Technology and Electronics Communication (IJCTEC), 5(3), 5146–5157.
20. Adari, V. K. (2020). Intelligent care at scale: AI-powered operations transforming hospital efficiency. International Journal of Engineering & Extended Technologies Research (IJEETR), 2(3), 1240–1249.
21. Keezhadath, A. A., Amarapalli, L., & Sethuraman, S. (2022). Scalable data lake architectures for multi-industry enterprise analytics. Essex Journal of AI Ethics and Responsible Innovation, 2, 136–175.
22. Nalini, T., Rama, A., Shanmuganathan, M., Sam, D., & Sheeba, D. A. (2022). Effective prediction of crop price using neuro evolutionary algorithm based on machine learning approach. Journal of Physics: Conference Series, 2251(1).
23. Chivukula, V. (2021). Impact of bias in incrementality measurement created on account of competing ads in auction-based digital ad delivery platforms. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 4(1), 4345–4350.
24. Rahman, M., Arif, M. H., Alim, M. A., Rahman, M. R., & Hossen, M. S. (2021). Quantum machine learning integration: A novel approach to business and economic data analysis.
25. Gaddapuri, N. S. (2022). Application of quantum computing in digital education systems. Power System Protection and Control, 50(2), 12–24.
26. Sreesaila, B., Abinaya, K., Swarnalatha, M., & Sugumar, R. (2018). Aadhaar card based health records monitoring system. International Journal of Innovative Research in Science, Engineering and Technology, 7(2).
27. Ananth, S., & Saranya, A. (2016). Reliability enhancement for cloud services: A survey. In 2016 International Conference on Computer Communication and Informatics (ICCCI) (pp. 1–7). IEEE.
28. Vimal Raja, G. (2021). Mining customer sentiments from financial feedback and reviews using data mining algorithms. International Journal of Innovative Research in Computer and Communication Engineering, 9(12), 14705–14710.
29. Adepu, R. (2021). Modernizing legacy data centers through virtualization and software-defined infrastructure. International Journal of Research and Applied Innovations (IJRAI), 4(4), 17–36.
30. Kasireddy, J. R. (2022). From Raw Trades to Audit-Ready Insights Designing Regulator-Grade Market Surveillance Pipelines. International Journal of Engineering & Extended Technologies Research (IJEETR), 4(2), 4609-4616.
31. Namdeo, A. (2022). Graph neural networks for real-time supply chain risk. International Journal of Humanities and Information Technology, 4(1–3), 175–192.
32. Panyala, V. R., & Pappu, H. (2021). Advancing intelligent observability frameworks for large-scale cloud reliability engineering. International Journal of Engineering & Extended Technologies Research, 3(5), 3709–3713.
33. Bellundagi, M. (2022). Performance Optimization Techniques for Enterprise Java Applications Using Middleware and Messaging Systems. International Journal of Computer Technology and Electronics Communication, 5(3), 5158-5168.
34. Adepu, G. (2021). AI-enabled digital identity verification framework for government self-service platforms using secure API and cloud integration. International Journal of Research Publications in Engineering, Technology and Management, 4(1), 160–176.
35. Rajakumari, S. B., Nalini, C., & Nalini, C. (2014). An efficient cost model for data storage with horizontal layout in the cloud. Indian Journal of Science and Technology, 7(3), 45–46.
36. Pujari, S. D., & Anusha, K. (2020). A review on prediction of autism using machine learning algorithm. International Journal of Advanced Science and Technology, 29(6), 4669–4678.
37. Kesavan, E. (2022). Driven learning and collaborative automation innovation via Trailhead and Tosca user groups. International Scientific Journal of Engineering and Management, 1(1).
38. Mohana, P., Muthuvinayagam, M., Umasankar, P., & Muthumanickam, T. (2022). Automation using artificial intelligence based natural language processing. In 2022 6th International Conference on Computing Methodologies and Communication (ICCMC) (pp. 1735–1739). IEEE.
39. Kamadi, S. (2022). Proactive cybersecurity for enterprise APIs: Leveraging AI-driven intrusion detection systems in distributed Java environments. International Journal of Research in Computer Applications and Information Technology (IJRCAIT), 5(1), 34–52.
40. Surisetty, L. S. (2021). Zero-trust data fabrics: A policy-driven model for secure cross-cloud healthcare and financial data exchanges. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 4(2), 4548–4556.