Security and Compliance Automation
DOI:
https://doi.org/10.63282/3117-5481/AIJCST-V7I5P105Keywords:
Security Automation, Compliance Monitoring, Risk Assessment, Policy Enforcement, Threat Detection, Vulnerability Management, Audit Automation, Access Control, Continuous Compliance, Incident Response, Governance Frameworks, Regulatory ReportingAbstract
The rapid increase of the digital infrastructure and the sophistication of the contemporary regulatory requirements have turned the compliance with the cybersecurity into a significant, yet increasingly difficult task on behalf of businesses. Conventional compliance administration, which is based on regular examinations, paper validation, and reactive responses, does not work due to the dynamism of cyber threats or emerging standards that include ISO 27001, NIST 800-53, and GDPR. The unified Security and Compliance Automation Framework proposed in this paper uses artificial intelligence (AI) and machine learning (ML) to automate compliance verification, policy enforcement, and threat response, using the DevSecOps-driven orchestration framework. The framework maximizes real-time ingestion of data, adaptive rule mapping, and proactive analytics to ensure continual observation of the hybrid and cloud-native infrastructures and control these platforms proactively.
Evaluations on experimental result of a controlled hybrid cloud testbed show that the solution applies better compliance measurements (up to 93 percent), shorten audit cycles (by 68 percent), and decreases the time to incident response (by 42 percent) than manual old-fashioned methods. Its modular design allows its use in areas beyond healthcare including finance and enterprise IT regarding enforcing security controls and policy alignment. Overall, these results highlight the possibility of the framework to create a self-regulating and resilient compliance ecosystem in such a way that organizations can move forward to no longer need response models on defense but remain on a framework of guaranteed regulatory compliance and operational security posture
References
[1] Anwar, Z., & Campbell, R. (2008, March). Automated assessment of compliance with security best practices. In International Conference on Critical Infrastructure Protection (pp. 173-187). Boston, MA: Springer US.
[2] Charmet, F., Tanuwidjaja, H. C., Ayoubi, S., Gimenez, P. F., Han, Y., Jmila, H., ... & Zhang, Z. (2022). Explainable artificial intelligence for cybersecurity: a literature survey. Annals of Telecommunications, 77(11), 789-812.
[3] Binbeshr, F., & Imam, M. (2025). Comparative Analysis of AI-Driven Security Approaches in DevSecOps: Challenges, Solutions, and Future Directions. arXiv preprint arXiv:2504.19154.
[4] Alghawli, A. S. A., & Radivilova, T. (2024). Resilient cloud cluster with DevSecOps security model, automates a data analysis, vulnerability search and risk calculation. Alexandria Engineering Journal, 107, 136-149.
[5] Reuben, J., Martucci, L. A., & Fischer-Hübner, S. (2015). Automated log audits for privacy compliance validation: a literature survey. IFIP International Summer School on Privacy and Identity Management, 312-326.
[6] Thota, R. C. (2024). Cloud-Native DevSecOps: Integrating Security Automation into CI/CD Pipelines. International Journal Of Innovative Research And Creative Technology, 10(6), 1-19.
[7] Folorunso, A., Adewumi, T., Adewa, A., Okonkwo, R., & Olawumi, T. N. (2024). Impact of AI on cybersecurity and security compliance. Global Journal of Engineering and Technology Advances, 21(01), 167-184.
[8] Rajapakse, R. N., Zahedi, M., & Babar, M. A. (2022). Collaborative application security testing for devsecops: An empirical analysis of challenges, best practices and tool support. arXiv preprint arXiv:2211.06953.
[9] Cheenepalli, J., Hastings, J. D., Ahmed, K. M., & Fenner, C. (2025, April). Advancing DevSecOps in SMEs: Challenges and Best Practices for Secure CI/CD Pipelines. In 2025 13th International Symposium on Digital Forensics and Security (ISDFS) (pp. 1-6). IEEE.
[10] Boutaba, R., & Aib, I. (2007). Policy-based management: A historical perspective. Journal of Network and Systems Management, 15(4), 447-480.
[11] Ullah, K. W., Ahmed, A. S., & Ylitalo, J. (2013, July). Towards building an automated security compliance tool for the cloud. In 2013 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (pp. 1587-1593). IEEE.
[12] Mir, A. W., & Ramachandran, R. K. (2021, July). Implementation of security orchestration, automation and response (SOAR) in smart grid-based SCADA systems. In Sixth International Conference on Intelligent Computing and Applications: Proceedings of ICICA 2020 (pp. 157-169). Singapore: Springer Singapore.
[13] Ali, S. M., Razzaque, A., Yousaf, M., & Shan, R. U. (2024). An automated compliance framework for critical infrastructure security through Artificial Intelligence. IEEE Access.
[14] Tunc, C., Hariri, S., Merzouki, M., Mahmoudi, C., De Vaulx, F. J., Chbili, J., ... & Battou, A. (2017, September). Cloud security automation framework. In 2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems (FAS* W) (pp. 307-312). IEEE.
[15] Bayani, S. V., Tillu, R., & Jeyaraman, J. (2023). Streamlining compliance: Orchestrating automated checks for cloud-based AI/ML workflows. Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online), 2(3), 413-435.
[16] Aydın, M. (2022). Automated Code Compliance Checking: A Meta-Analysis. Automation and control: Theories and applications, 39.
[17] Scherer, M. U. (2015). Regulating artificial intelligence systems: Risks, challenges, competencies, and strategies. Harv. JL & Tech., 29, 353.
[18] Rusum, G. P., Pappula, K. K., & Anasuri, S. (2020). Constraint Solving at Scale: Optimizing Performance in Complex Parametric Assemblies. International Journal of Emerging Trends in Computer Science and Information Technology, 1(2), 47-55. https://doi.org/10.63282/3050-9246.IJETCSIT-V1I2P106
[19] Pappula, K. K. (2020). Browser-Based Parametric Modeling: Bridging Web Technologies with CAD Kernels. International Journal of Emerging Trends in Computer Science and Information Technology, 1(3), 56-67. https://doi.org/10.63282/3050-9246.IJETCSIT-V1I3P107
[20] Rahul, N. (2020). Vehicle and Property Loss Assessment with AI: Automating Damage Estimations in Claims. International Journal of Emerging Research in Engineering and Technology, 1(4), 38-46. https://doi.org/10.63282/3050-922X.IJERET-V1I4P105
[21] Enjam, G. R., & Chandragowda, S. C. (2020). Role-Based Access and Encryption in Multi-Tenant Insurance Architectures. International Journal of Emerging Trends in Computer Science and Information Technology, 1(4), 58-66. https://doi.org/10.63282/3050-9246.IJETCSIT-V1I4P107
[22] Pappula, K. K., & Anasuri, S. (2021). API Composition at Scale: GraphQL Federation vs. REST Aggregation. International Journal of Emerging Trends in Computer Science and Information Technology, 2(2), 54-64. https://doi.org/10.63282/3050-9246.IJETCSIT-V2I2P107
[23] Pedda Muntala, P. S. R. (2021). Integrating AI with Oracle Fusion ERP for Autonomous Financial Close. International Journal of AI, BigData, Computational and Management Studies, 2(2), 76-86. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V2I2P109
[24] Rahul, N. (2021). AI-Enhanced API Integrations: Advancing Guidewire Ecosystems with Real-Time Data. International Journal of Emerging Research in Engineering and Technology, 2(1), 57-66. https://doi.org/10.63282/3050-922X.IJERET-V2I1P107
[25] Enjam, G. R., Chandragowda, S. C., & Tekale, K. M. (2021). Loss Ratio Optimization using Data-Driven Portfolio Segmentation. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 2(1), 54-62. https://doi.org/10.63282/3050-9262.IJAIDSML-V2I1P107
[26] Rusum, G. P. (2022). Security-as-Code: Embedding Policy-Driven Security in CI/CD Workflows. International Journal of AI, BigData, Computational and Management Studies, 3(2), 81-88. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V3I2P108
[27] Pappula, K. K. (2022). Modular Monoliths in Practice: A Middle Ground for Growing Product Teams. International Journal of Emerging Trends in Computer Science and Information Technology, 3(4), 53-63. https://doi.org/10.63282/3050-9246.IJETCSIT-V3I4P106
[28] Jangam, S. K. (2022). Role of AI and ML in Enhancing Self-Healing Capabilities, Including Predictive Analysis and Automated Recovery. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 3(4), 47-56. https://doi.org/10.63282/3050-9262.IJAIDSML-V3I4P106
[29] Anasuri, S., Rusum, G. P., & Pappula, kiran K. (2022). Blockchain-Based Identity Management in Decentralized Applications. International Journal of AI, BigData, Computational and Management Studies, 3(3), 70-81. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V3I3P109
[30] Pedda Muntala, P. S. R. (2022). Natural Language Querying in Oracle Fusion Analytics: A Step toward Conversational BI. International Journal of Emerging Trends in Computer Science and Information Technology, 3(3), 81-89. https://doi.org/10.63282/3050-9246.IJETCSIT-V3I3P109
[31] Rahul, N. (2022). Enhancing Claims Processing with AI: Boosting Operational Efficiency in P&C Insurance. International Journal of Emerging Trends in Computer Science and Information Technology, 3(4), 77-86. https://doi.org/10.63282/3050-9246.IJETCSIT-V3I4P108
[32] Enjam, G. R., & Tekale, K. M. (2022). Predictive Analytics for Claims Lifecycle Optimization in Cloud-Native Platforms. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 3(1), 95-104. https://doi.org/10.63282/3050-9262.IJAIDSML-V3I1P110
[33] Tekale, K. M. (2022). Claims Optimization in a High-Inflation Environment Provide Frameworks for Leveraging Automation and Predictive Analytics to Reduce Claims Leakage and Accelerate Settlements. International Journal of Emerging Research in Engineering and Technology, 3(2), 110-122. https://doi.org/10.63282/3050-922X.IJERET-V3I2P112
[34] Rusum, G. P. (2023). Secure Software Supply Chains: Managing Dependencies in an AI-Augmented Dev World. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 4(3), 85-97. https://doi.org/10.63282/3050-9262.IJAIDSML-V4I3P110
[35] Pappula, K. K., & Rusum, G. P. (2023). Multi-Modal AI for Structured Data Extraction from Documents. International Journal of Emerging Research in Engineering and Technology, 4(3), 75-86. https://doi.org/10.63282/3050-922X.IJERET-V4I3P109
[36] Jangam, S. K., & Karri, N. (2023). Robust Error Handling, Logging, and Monitoring Mechanisms to Effectively Detect and Troubleshoot Integration Issues in MuleSoft and Salesforce Integrations. International Journal of Emerging Research in Engineering and Technology, 4(4), 80-89. https://doi.org/10.63282/3050-922X.IJERET-V4I4P108
[37] Anasuri, S. (2023). Synthetic Identity Detection Using Graph Neural Networks. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 4(4), 87-96. https://doi.org/10.63282/3050-9262.IJAIDSML-V4I4P110
[38] Pedda Muntala, P. S. R. (2023). AI-Powered Chatbots and Digital Assistants in Oracle Fusion Applications. International Journal of Emerging Trends in Computer Science and Information Technology, 4(3), 101-111. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I3P111
[39] Rahul, N. (2023). Personalizing Policies with AI: Improving Customer Experience and Risk Assessment. International Journal of Emerging Trends in Computer Science and Information Technology, 4(1), 85-94. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I1P110
[40] Enjam, G. R. (2023). Optimizing PostgreSQL for High-Volume Insurance Transactions & Secure Backup and Restore Strategies for Databases. International Journal of Emerging Trends in Computer Science and Information Technology, 4(1), 104-111. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I1P112
[41] Tekale, K. M. (2023). Cyber Insurance Evolution: Addressing Ransomware and Supply Chain Risks. International Journal of Emerging Trends in Computer Science and Information Technology, 4(3), 124-133. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I3P113
[42] Rusum, G. P. (2024). Trustworthy AI in Software Systems: From Explainability to Regulatory Compliance. International Journal of Emerging Research in Engineering and Technology, 5(1), 71-81. https://doi.org/10.63282/3050-922X.IJERET-V5I1P109
[43] Enjam, G. R., & Tekale, K. M. (2024). Self-Healing Microservices for Insurance Platforms: A Fault-Tolerant Architecture Using AWS and PostgreSQL. International Journal of AI, BigData, Computational and Management Studies, 5(1), 127-136. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V5I1P113
[44] Kiran Kumar Pappula, "Transformer-Based Classification of Financial Documents in Hybrid Workflows" International Journal of Multidisciplinary on Science and Management, Vol. 1, No. 3, pp. 48-61, 2024.
[45] Rahul, N. (2024). Revolutionizing Medical Bill Reviews with AI: Enhancing Claims Processing Accuracy and Efficiency. International Journal of AI, BigData, Computational and Management Studies, 5(2), 128-140. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V5I2P113
[46] Partha Sarathi Reddy Pedda Muntala, "AI-Powered Expense and Procurement Automation in Oracle Fusion Cloud" International Journal of Multidisciplinary on Science and Management, Vol. 1, No. 3, pp. 62-75, 2024.
[47] Jangam, S. K. (2024). Advancements and Challenges in Using AI and ML to Improve API Testing Efficiency, Coverage, and Effectiveness. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 5(2), 95-106. https://doi.org/10.63282/3050-9262.IJAIDSML-V5I2P111
[48] Anasuri, S. (2024). Secure Software Development Life Cycle (SSDLC) for AI-Based Applications. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 5(1), 104-116. https://doi.org/10.63282/3050-9262.IJAIDSML-V5I1P110
[49] Tekale, K. M., & Rahul, N. (2024). AI Bias Mitigation in Insurance Pricing and Claims Decisions. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 5(1), 138-148. https://doi.org/10.63282/3050-9262.IJAIDSML-V5I1P113
[50] Pappula, K. K., & Rusum, G. P. (2020). Custom CAD Plugin Architecture for Enforcing Industry-Specific Design Standards. International Journal of AI, BigData, Computational and Management Studies, 1(4), 19-28. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V1I4P103
[51] Rahul, N. (2020). Optimizing Claims Reserves and Payments with AI: Predictive Models for Financial Accuracy. International Journal of Emerging Trends in Computer Science and Information Technology, 1(3), 46-55. https://doi.org/10.63282/3050-9246.IJETCSIT-V1I3P106
[52] Enjam, G. R., & Tekale, K. M. (2020). Transitioning from Monolith to Microservices in Policy Administration. International Journal of Emerging Research in Engineering and Technology, 1(3), 45-52. https://doi.org/10.63282/3050-922X.IJERETV1I3P106
[53] Pappula, K. K., & Rusum, G. P. (2021). Designing Developer-Centric Internal APIs for Rapid Full-Stack Development. International Journal of AI, BigData, Computational and Management Studies, 2(4), 80-88. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V2I4P108
[54] Pedda Muntala, P. S. R., & Jangam, S. K. (2021). End-to-End Hyperautomation with Oracle ERP and Oracle Integration Cloud. International Journal of Emerging Research in Engineering and Technology, 2(4), 59-67. https://doi.org/10.63282/3050-922X.IJERET-V2I4P107
[55] Rahul, N. (2021). Strengthening Fraud Prevention with AI in P&C Insurance: Enhancing Cyber Resilience. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 2(1), 43-53. https://doi.org/10.63282/3050-9262.IJAIDSML-V2I1P106
[56] Enjam, G. R., & Chandragowda, S. C. (2021). RESTful API Design for Modular Insurance Platforms. International Journal of Emerging Research in Engineering and Technology, 2(3), 71-78. https://doi.org/10.63282/3050-922X.IJERET-V2I3P108
[57] Rusum, G. P., & Pappula, kiran K. . (2022). Event-Driven Architecture Patterns for Real-Time, Reactive Systems. International Journal of Emerging Research in Engineering and Technology, 3(3), 108-116. https://doi.org/10.63282/3050-922X.IJERET-V3I3P111
[58] Pappula, K. K. (2022). Containerized Zero-Downtime Deployments in Full-Stack Systems. International Journal of AI, BigData, Computational and Management Studies, 3(4), 60-69. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V3I4P107
[59] Jangam, S. K., & Karri, N. (2022). Potential of AI and ML to Enhance Error Detection, Prediction, and Automated Remediation in Batch Processing. International Journal of AI, BigData, Computational and Management Studies, 3(4), 70-81. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V3I4P108
[60] Anasuri, S. (2022). Formal Verification of Autonomous System Software. International Journal of Emerging Research in Engineering and Technology, 3(1), 95-104. https://doi.org/10.63282/3050-922X.IJERET-V3I1P110
[61] Pedda Muntala, P. S. R., & Jangam, S. K. (2022). Predictive Analytics in Oracle Fusion Cloud ERP: Leveraging Historical Data for Business Forecasting. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 3(4), 86-95. https://doi.org/10.63282/3050-9262.IJAIDSML-V3I4P110
[62] Rahul, N. (2022). Optimizing Rating Engines through AI and Machine Learning: Revolutionizing Pricing Precision. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 3(3), 93-101. https://doi.org/10.63282/3050-9262.IJAIDSML-V3I3P110
[63] Enjam, G. R. (2022). Secure Data Masking Strategies for Cloud-Native Insurance Systems. International Journal of Emerging Trends in Computer Science and Information Technology, 3(2), 87-94. https://doi.org/10.63282/3050-9246.IJETCSIT-V3I2P109
[64] Tekale, K. M. T., & Enjam, G. reddy . (2022). The Evolving Landscape of Cyber Risk Coverage in P&C Policies. International Journal of Emerging Trends in Computer Science and Information Technology, 3(3), 117-126. https://doi.org/10.63282/3050-9246.IJETCSIT-V3I1P113
[65] Rusum, G. P., & Anasuri, S. (2023). Synthetic Test Data Generation Using Generative Models. International Journal of Emerging Trends in Computer Science and Information Technology, 4(4), 96-108. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I4P111
[66] Pappula, K. K. (2023). Edge-Deployed Computer Vision for Real-Time Defect Detection. International Journal of AI, BigData, Computational and Management Studies, 4(3), 72-81. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V4I3P108
[67] Jangam, S. K. (2023). Data Architecture Models for Enterprise Applications and Their Implications for Data Integration and Analytics. International Journal of Emerging Trends in Computer Science and Information Technology, 4(3), 91-100. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I3P110
[68] Anasuri, S., Rusum, G. P., & Pappula, K. K. (2023). AI-Driven Software Design Patterns: Automation in System Architecture. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 4(1), 78-88. https://doi.org/10.63282/3050-9262.IJAIDSML-V4I1P109
[69] Pedda Muntala, P. S. R., & Karri, N. (2023). Managing Machine Learning Lifecycle in Oracle Cloud Infrastructure for ERP-Related Use Cases. International Journal of Emerging Research in Engineering and Technology, 4(3), 87-97. https://doi.org/10.63282/3050-922X.IJERET-V4I3P110
[70] Rahul, N. (2023). Transforming Underwriting with AI: Evolving Risk Assessment and Policy Pricing in P&C Insurance. International Journal of AI, BigData, Computational and Management Studies, 4(3), 92-101. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V4I3P110
[71] Enjam, G. R., Tekale, K. M., & Chandragowda, S. C. (2023). Zero-Downtime CI/CD Production Deployments for Insurance SaaS Using Blue/Green Deployments. International Journal of Emerging Research in Engineering and Technology, 4(3), 98-106. https://doi.org/10.63282/3050-922X.IJERET-V4I3P111
[72] Tekale , K. M. (2023). AI-Powered Claims Processing: Reducing Cycle Times and Improving Accuracy. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 4(2), 113-123. https://doi.org/10.63282/3050-9262.IJAIDSML-V4I2P113
[73] Rusum, G. P., & Anasuri, S. (2024). Vector Databases in Modern Applications: Real-Time Search, Recommendations, and Retrieval-Augmented Generation (RAG). International Journal of AI, BigData, Computational and Management Studies, 5(4), 124-136. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V5I4P113
[74] Enjam, G. R. (2024). AI-Powered API Gateways for Adaptive Rate Limiting and Threat Detection. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 5(4), 117-129. https://doi.org/10.63282/3050-9262.IJAIDSML-V5I4P112
[75] Pappula, K. K., & Rusum, G. P. (2024). AI-Assisted Address Validation Using Hybrid Rule-Based and ML Models. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 5(4), 91-104. https://doi.org/10.63282/3050-9262.IJAIDSML-V5I4P110
[76] Rahul, N. (2024). Improving Policy Integrity with AI: Detecting Fraud in Policy Issuance and Claims. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 5(1), 117-129. https://doi.org/10.63282/3050-9262.IJAIDSML-V5I1P111
[77] Reddy Pedda Muntala, P. S., & Jangam, S. K. (2024). Automated Risk Scoring in Oracle Fusion ERP Using Machine Learning. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 5(4), 105-116. https://doi.org/10.63282/3050-9262.IJAIDSML-V5I4P111
[78] Jangam, S. K. (2024). Scalability and Performance Limitations of Low-Code and No-Code Platforms for Large-Scale Enterprise Applications and Solutions. International Journal of Emerging Trends in Computer Science and Information Technology, 5(3), 68-78. https://doi.org/10.63282/3050-9246.IJETCSIT-V5I3P107
[79] Anasuri, S., & Rusum, G. P. (2024). Software Supply Chain Security: Policy, Tooling, and Real-World Incidents. International Journal of Emerging Trends in Computer Science and Information Technology, 5(3), 79-89. https://doi.org/10.63282/3050-9246.IJETCSIT-V5I3P108
[80] Tekale, K. M. (2024). Generative AI in P&C: Transforming Claims and Customer Service. International Journal of Emerging Trends in Computer Science and Information Technology, 5(2), 122-131. https://doi.org/10.63282/3050-9246.IJETCSIT-V5I2P113
