Adaptive Cybersecurity Frameworks for Enterprise Systems Integrating Artificial Intelligence in Cloud Environments

Bernhard Plattner

doi:10.15662/IJRAI.2026.0902009

Authors

Bernhard Plattner Professor of Computer Engineering, ETH Zurich, Switzerland Author

DOI:

https://doi.org/10.15662/IJRAI.2026.0902009

Keywords:

Adaptive cybersecurity, artificial intelligence, cloud computing, enterprise security, machine learning, threat detection, automated response, cyber resilience, cloud security frameworks, behavioral analytics

Abstract

The rapid adoption of cloud computing and artificial intelligence (AI) has transformed enterprise systems, enabling scalability, automation, and data-driven decision-making. However, this convergence introduces complex cybersecurity challenges, including dynamic threat landscapes, sophisticated cyberattacks, and increased attack surfaces. Traditional static security frameworks are insufficient to address these evolving risks. This study explores adaptive cybersecurity frameworks that integrate AI to enhance threat detection, response, and resilience in cloud environments. The research emphasizes the role of machine learning, behavioral analytics, and automated incident response in creating self-learning security systems capable of real-time adaptation. By examining current models and proposing an adaptive framework, this work highlights how enterprises can strengthen their security posture while maintaining operational efficiency. The study also discusses implementation challenges such as data privacy, model bias, and integration complexity. Ultimately, adaptive cybersecurity frameworks represent a paradigm shift from reactive to proactive security strategies, enabling enterprises to anticipate and mitigate threats effectively. This research contributes to the growing body of knowledge on intelligent security systems and provides practical insights for organizations seeking to secure AI-driven cloud infrastructures.

References

1. Padala, S. (2023). Intelligent Workforce Management: A Predictive Analytics Approach. American International Journal of Computer Science and Technology, 5(3), 42-47.

2. Barigidad, S., Hameed, S., Karri, N., Jangam, S. K., Pedda, P. S. R., & Gupta, D. (2025, December). Computational Modeling of AI-Enhanced Learning Pathways: A Mathematical Framework for Optimizing Knowledge Acquisition, Cognitive Load Management, and Student Performance in STEM Education. In 2025 International Conference on AI-Driven STEM Education and Learning Technologies (AISTEMEDU) (pp. 1-7). IEEE.

3. Anujaa, T., Thajudeen Ali Ahamed, A. F., Baranwal, V., Thanikaiselvan, V., Subashanthini, S., Sivaranjani Devi, C., & Rengarajan, A. (2025). A lightweight multi round confusion-diffusion cryptosystem for securing images using a modified 5D chaotic system. Scientific Reports, 15(1), 31986.

4. Vayyasi, N. K. (2023). Retail fraud analytics using generative intelligence and Java cloud frameworks. International Journal of Science, Research and Technology (IJSRAT), 6(4), 10324–10337.

5. Adari, V. K. (2025). Architectural Frameworks for AI-Enhanced Cloud Systems in Large-Scale Enterprise Deployments Vijay Kumar Adari Cognizant Technology Solutions, USA. International Journal of Computer Technology and Electronics Communication, 8(6), 11791-11798.

6. Cherukuri, B. R. (2024, February). Development of Design Patterns with Adaptive User Interface for Cloud Native Microservice Architecture Using Deep Learning With IoT. In 2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT) (Vol. 5, pp. 1866-1871). IEEE.

7. Gupta, S. Digital Twins for Circular Economy Optimization: A Framework for Sustainable Engineering Systems. Proceedings 2025, 121, 4. [CrossRef]

8. Sahid, M. H., Pratama, D. A., Abd Rahman, M., Vardhani, A. K., Kulsum, D. U., Tanaka, J., ... & Renaldi, T. (2026). Kesehatan Masyarakat Di Era Digital. CV Eureka Media Aksara.

9. Gopinathan, V. R. (2025). Software engineering practices for AI-driven systems: From development to deployment (MLOps perspective). International Journal of Science, Research and Technology (IJSRAT), 8(1), 13493–13500. https://doi.org/10.15662/IJSRAT.2025.0801002

10. Tailor, P., & Kale, A. (2025). Multimodal sentiment analysis of earnings calls and SEC filings: A deep learning approach to financial disclosures. Utilitas Mathematica, 122, 3163-3168.

11. Aarthi, K., Thirumoorthy, P., Tamizharasu, K., Manoja, R., Kalyanasundaram, P., & Rajasekar, M. (2025, September). Improved Network lifetime using Cluster based Power-Aware Balanced Routing Protocol for Device to Device Communication. In 2025 6th International Conference on Electronics and Sustainable Communication Systems (ICESC) (pp. 1005-1010). IEEE.

12. Mudunuri, P. R. (2023). Governance-Aware Infrastructure-as-Code for Regulated Research Environments. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(4), 9017-9027.

13. Gurram, S. (2025). Executable Data Contracts for Reliable AI Pipelines. International Journal of Computer Technology and Electronics Communication, 8(6), 504-525.

14. Karthikeyan, K., & Umasankar, P. (2025). A novel Buck-Boost Modified Series Forward (BBMSF) converter for enhanced efficiency in hybrid renewable energy systems. Ain Shams Engineering Journal, 16(10), 103557.

15. Ganesh, N., Sriram, A., Krishnan, S. N., & Rao, T. S. (2025, June). Simultaneous Enhancement and Detection of Brain Tumors Using GAN. In Intelligent Computing-Proceedings of the Computing Conference (pp. 206-220). Cham: Springer Nature Switzerland.

16. Md Shahadat Hossain, M. S. H., Md Shahdat Hossain, M. S. H., Mohammad Ali, M. A., & Md Whahidur Rahman, M. W. R. (2025). Machine Learning-Based Analytics Framework for Detecting Tax Evasion and Financial Misconduct in US Enterprises. Machine Learning-Based Analytics Framework for Detecting Tax Evasion and Financial Misconduct in US Enterprises, 2(12), 114-138.

17. Sugumar, R. (2025). Designing Resilient and Scalable Cloud-Native Frameworks for Generative AI Content Production. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 8(6), 13268-13279.

18. Gentyala, R. (2021). Bridging the Semantic Gap: A Lightweight Ontological Framework for Real-Time Harmonization of Consumer Wearable Data with FHIR-Based EHR Systems. IACSE-International Journal of Computer Technology (IACSE-IJCT), 2(1), 24-77.

19. Soundappan, S. J. (2024). AI-Driven Customer Intelligence in Enterprise Lakehouse Systems Sentiment Mining Governance-Aware Analytics and Real-Time Data Synchronization. International Journal of Advanced Engineering Science and Information Technology (IJAESIT), 7(5), 14905.

20. Kiran, A., Rubini, P., & Kumar, S. S. (2025). Comprehensive review of privacy, utility and fairness offered by synthetic data. IEEE Access.

21. Pradhan, C., & Trehan, A. (2025). Integration of blockchain technology in secure data engineering workflows. International Journal of Computer Sciences and Engineering, 13(1), 01-07.

22. Kunadi, S. K. (2025). Enterprise Data Engineering Innovations: Unifying Customer and Revenue Data Platforms. International Journal of Engineering & Extended Technologies Research (IJEETR), 7(6), 11219-11228.

23. Mahzabin Binte, R., Mohammad, Y., & Md Parvez, A. (2024). Data-Driven Population Health Analytics for Identifying High-Risk Groups and Health Disparities. Data-Driven Population Health Analytics for Identifying High-Risk Groups and Health Disparities, 1(11), 58-82.

24. Hasib, A., Akib, A. S. M., Ankur, N. D., & Giri, A. (2026). Dual-Modality IoT Framework for Integrated Access Control and Environmental Safety Monitoring with Real-Time Cloud Analytics. arXiv preprint arXiv:2601.20366.

25. Mathew, A. (2024). From Conversation to Command Execution: A Comparative Threat Modeling and Risk Analysis of OpenClaw and ChatGPT. Risk, 100(1).

26. Singh, A. (2023). Network slicing and its testing in 5G networks. International Journal of Computer Technology and Electronics Communication, 6(6), 8005-8013.

27. Karvannan, R. (2025). Architecting DSCSA-compliant systems for real-time inventory management in high-volume retail pharmacy networks. International Journal of Computer Engineering and Technology, 16(2), 4181–4194. https://doi.org/10.34218/IJCET_16_02_036

28. Praveena, M., Saravanan, M., & Yerra, R. (2025, June). PSO MPPT based Control Framework for Photovoltaic Systems to enhance Power Quality. In 2025 5th International Conference on Intelligent Technologies (CONIT) (pp. 1-5). IEEE.

29. Vimal, V. R. (2025). Hybrid Nature-Inspired Optimization and Machine Learning Techniques for Cardiac Disease Detection. SGS-Engineering & Sciences, 1(3).

30. Sundaresh, G., Ramesh, S., Malarvizhi, K., & Nagarajan, C. (2025, April). Artificial Intelligence Based Smart Water Quality Monitoring System with Electrocoagulation Technique. In 2025 3rd International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA) (pp. 1-6). IEEE.

31. Appani, C. (2025). AI-Powered Threat Detection In Real-Time Payment Systems. International Journal of Environmental Sciences.

32. Jabed, M. M. I., Ferdous, S., Ankhi, R. B., Gupta, A. B., & Hossain, M. S. (2025). AI-Driven Intrusion Detection Systems: A Business Analyst’s Framework for Enhancing Enterprise Security and Intelligence. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 8(5), 12708-12719.

33. Niture, N., & Abdellatif, I. (2025). A systematic review of factors, data sources, and prediction techniques for earlier prediction of traffic collision using AI and machine learning. Multimedia Tools and Applications, 84(18), 19009-19037.

34. Anbazhagan, K. (2025). Secure AI Enabled Enterprise Ecosystems for Fraud Prevention Compliance Automation and Real Time Analytics. International Journal of Multidisciplinary Research in Science, Engineering, Technology & Management, 1(4), 6-13

35. Dave, B. L. (2024). Harnessing Artificial Intelligence for Salesforce Metadata Advanced Migration Strategies and Strategic Business Benefits. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 7(6), 11398-11408.

36. Poornima, G., & Anand, L. (2025). Medical image fusion model using CT and MRI images based on dual scale weighted fusion based residual attention network with encoder-decoder architecture. Biomedical Signal Processing and Control, 108, 107932.

37. Rahman, M. B., Ahmad, S., Kanojiya, S., Yasin, M., & Hasan, M. (2025). Cost-Effective Healthcare Operations: Financial Modeling and Optimization Using Business Intelligence Tools. Nvpubhouse Library for International Journal of Medical Science and Public Health Research, 6(10), 80-106.

38. Jamaesha, S. S., Gowtham, M. S., Ramkumar, M., & Vigenesh, M. (2025). Optimized Auto Separate Federated Graph Neural With Enhanced Well‐Known Signature Trust‐Based Routing Attacks Detection in Internet of Things. Transactions on Emerging Telecommunications Technologies, 36(5), e70158.