Volume 1 Issue 3 | 2024 | View PDF
Paper Id:IJMSM-V1I3P106
doi: 10.71141/30485037/V1I3P106

Comprehensive Defense-in-Depth Strategy for Enterprise Application Security

Sandeep Kumar Jangam, Partha Sarathi Reddy Pedda Muntala

Citation:
Sandeep Kumar Jangam, Partha Sarathi Reddy Pedda Muntala, "Comprehensive Defense-in-Depth Strategy for Enterprise Application Security" International Journal of Multidisciplinary on Science and Management, Vol. 1, No. 3, pp. 62-75, 2024.

Abstract:
Enterprise applications require a layered defense-in-depth approach to address a complex cybersecurity environment. Organizations are exposed to such a wide range of threats, including those caused by an insider, as well as zero-day or Developed Persistent Threats (APTs). The paper has offered a multi-layered strategy where policy and technology, along with human-centric measures, are all combined to offer a secure architecture of enterprise applications. Upholding the concept of defence in depth, the plan also incorporates, at its outermost layer, perimeter safeguards, network segmentation, endpoint security, application-based controls, and data encryption, all backed by continuous threat intelligence and tracking. The most important technological supports include the use of Intrusion Detection Systems (IDS), Web Application Firewalls (WAF), secure coding principles, microsegmentation, and behavioural analytics. The paper also included a literature review to evaluate trends in the development of enterprise security architectures, major gaps, and emerging trends in this area. In our methodology section, we explain the way these elements are chosen, combined and optimized in the actual enterprise environment. We examine the effectiveness of the proposed strategy in addressing these issues through a case study simulation of a medium-sized enterprise architecture. The outcome shows that the theaterium has demonstrated a significant increase in threat recognition, response time, and system resilience. It discusses cost-effectiveness, compliance, and scalability, with the conclusion supporting the need for an adaptable and proactive security posture. The results serve as a guide for CISOs and IT security departments to adopt a well-fortified defence model in-depth

Keywords: Defense-in-Depth, Enterprise Application Security, Intrusion Detection, Secure Architecture, Threat Intelligence, Layered Security, Data Protection.

References:
1. Force, J. T. (2017). Security and privacy controls for information systems and organizations (No. NIST Special Publication (SP) 800-53 Rev. 5 (Withdrawn)). National Institute of Standards and Technology.
2. Saltzer, J. H., & Schroeder, M. D. (1975). The protection of information in computer systems. Proceedings of the IEEE, 63(9), 1278-1308.
3. Shostack, A. (2014). Threat modeling: Designing for security. John wiley & sons.
4. Scarfone, K., & Mell, P. (2007). Guide to intrusion detection and prevention systems (IDSs). NIST special publication, 800(2007), 94.
5. Fabro, M. (2007). Control systems cyber security: Defence-in-depth strategies (No. INL/CON-07-12804). Idaho National Lab.(INL), Idaho Falls, ID (United States).
6. Holmberg, J. E. (2017). Defense‐in‐Depth. Handbook of safety principles, 42-62.
7. Kang, M. H., & Froscher, J. N. (2000). A Strategy of Security Services for Enterprise Applications (No. NRLMR5540008478).
8. Anderson, E. E., & Choobineh, J. (2008). Enterprise information security strategies. Computers & security, 27(1-2), 22-29.
9. May, C. J., Hammerstein, J., Mattson, J., & Rush, K. (2006). Defense in depth: foundation for secure and resilient it enterprises (No. CMUSEI2006HB003).
10. Psounis, K. (2009). Active networks: Applications, security, safety, and architectures. IEEE Communications Surveys, 2(1), 2-16.
11. Heidari, A., & Jabraeil Jamali, M. A. (2023). Internet of Things intrusion detection systems: a comprehensive review and future directions. Cluster Computing, 26(6), 3753-3780.
12. Said, A., Yahyaoui, A., & Abdellatif, T. (2023, November). HIPAA and GDPR compliance in IoT healthcare systems. In International Conference on Model and Data Engineering (pp. 198-209). Cham: Springer Nature Switzerland.
13. Lin, H., Yan, Z., Chen, Y., & Zhang, L. (2018). A survey on network security-related data collection technologies. IEE Access, 6, 18345-18365.
14. Göksel, U. Ç. T. U., ALKAN, M., Doğru, İ. A., & Dörterler, M. (2019, October). Perimeter network security solutions: A survey. In 2019, 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 1-6). IEEE.
15. Northcutt, S., Zeltser, L., Winters, S., Kent, K., & Ritchey, R. W. (2005). Inside Network Perimeter Security (Inside). Sams.
16. Scalas, M., & Giacinto, G. (2019, October). Automotive cybersecurity: Foundations for next-generation vehicles. In 2019, the 2nd International Conference on New Trends in Computing Sciences (ICTCS) (pp. 1-6). IEEE.
17. Jonnaganti, V. (2009). An Integrated Security Model for the Management of SOA Improving the attractiveness of SOA Environments through a strong Architectural Integrity (Master's thesis).
18. Crauder, D., Solecky, E., & Emans, J. (2016, May). Reducing metrology mean-time-to-detect by utilizing product data. In 2016, the 27th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) (pp. 423-428). IEEE.
19. Aguilar, A. (2023). Lowering Mean Time to Recovery (MTTR) in Responding to System Downtime or Outages: An Application of Lean Six Sigma Methodology. In the 13th Annual International Conference on Industrial Engineering and Operations Management.
20. Mavroeidakos, T., Michalas, A., & Vergados, D. D. (2016, April). Security architecture based on defence-in-depth for cloud computing environments. In 2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) (pp. 334-339). IEEE.
21. 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
22. Pappula, K. K., & Anasuri, S. (2020). A Domain-Specific Language for Automating Feature-Based Part Creation in Parametric CAD. International Journal of Emerging Research in Engineering and Technology, 1(3), 35-44. https://doi.org/10.63282/3050-922X.IJERET-V1I3P105
23. 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
24. Enjam, G. R. (2020). Ransomware Resilience and Recovery Planning for Insurance Infrastructure. International Journal of AI, BigData, Computational and Management Studies, 1(4), 29-37. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V1I4P104
25. Pappula, K. K., Anasuri, S., & Rusum, G. P. (2021). Building Observability into Full-Stack Systems: Metrics That Matter. International Journal of Emerging Research in Engineering and Technology, 2(4), 48-58. https://doi.org/10.63282/3050-922X.IJERET-V2I4P106
26. Pedda Muntala, P. S. R., & Karri, N. (2021). Leveraging Oracle Fusion ERP’s Embedded AI for Predictive Financial Forecasting. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 2(3), 74-82. https://doi.org/10.63282/3050-9262.IJAIDSML-V2I3P108
27. 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
28. Enjam, G. R. (2021). Data Privacy & Encryption Practices in Cloud-Based Guidewire Deployments. International Journal of AI, BigData, Computational and Management Studies, 2(3), 64-73. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V2I3P108
29. Rusum, G. P. (2022). WebAssembly across Platforms: Running Native Apps in the Browser, Cloud, and Edge. International Journal of Emerging Trends in Computer Science and Information Technology, 3(1), 107-115. https://doi.org/10.63282/3050-9246.IJETCSIT-V3I1P112
30. Pappula, K. K. (2022). Architectural Evolution: Transitioning from Monoliths to Service-Oriented Systems. International Journal of Emerging Research in Engineering and Technology, 3(4), 53-62. https://doi.org/10.63282/3050-922X.IJERET-V3I4P107
31. Anasuri, S. (2022). Adversarial Attacks and Defenses in Deep Neural Networks. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 3(4), 77-85. https://doi.org/10.63282/xs971f03
32. Pedda Muntala, P. S. R. (2022). Anomaly Detection in Expense Management using Oracle AI Services. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 3(1), 87-94. https://doi.org/10.63282/3050-9262.IJAIDSML-V3I1P109
33. Rahul, N. (2022). Automating Claims, Policy, and Billing with AI in Guidewire: Streamlining Insurance Operations. International Journal of Emerging Research in Engineering and Technology, 3(4), 75-83. https://doi.org/10.63282/3050-922X.IJERET-V3I4P109
34. Enjam, G. R. (2022). Energy-Efficient Load Balancing in Distributed Insurance Systems Using AI-Optimized Switching Techniques. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 3(4), 68-76. https://doi.org/10.63282/3050-9262.IJAIDSML-V3I4P108
35. Rusum, G. P., & Anasuri, S. (2023). Composable Enterprise Architecture: A New Paradigm for Modular Software Design. International Journal of Emerging Research in Engineering and Technology, 4(1), 99-111. https://doi.org/10.63282/3050-922X.IJERET-V4I1P111
36. Pappula, K. K. (2023). Reinforcement Learning for Intelligent Batching in Production Pipelines. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 4(4), 76-86. https://doi.org/10.63282/3050-9262.IJAIDSML-V4I4P109
37. Anasuri, S. (2023). Secure Software Supply Chains in Open-Source Ecosystems. International Journal of Emerging Trends in Computer Science and Information Technology, 4(1), 62-74. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I1P108
38. Pedda Muntala, P. S. R., & Karri, N. (2023). Leveraging Oracle Digital Assistant (ODA) to Automate ERP Transactions and Improve User Productivity. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 4(4), 97-104. https://doi.org/10.63282/3050-9262.IJAIDSML-V4I4P111
39. 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
40. Enjam, G. R. (2023). Modernizing Legacy Insurance Systems with Microservices on Guidewire Cloud Platform. International Journal of Emerging Research in Engineering and Technology, 4(4), 90-100. https://doi.org/10.63282/3050-922X.IJERET-V4I4P109
41. 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
42. 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
43. 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
44. Pappula, K. K. (2021). Modern CI/CD in Full-Stack Environments: Lessons from Source Control Migrations. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 2(4), 51-59. https://doi.org/10.63282/3050-9262.IJAIDSML-V2I4P106
45. Pedda Muntala, P. S. R. (2021). Prescriptive AI in Procurement: Using Oracle AI to Recommend Optimal Supplier Decisions. International Journal of AI, BigData, Computational and Management Studies, 2(1), 76-87. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V2I1P108
46. 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
47. 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
48. Rusum, G. P., & Pappula, K. K. (2022). Federated Learning in Practice: Building Collaborative Models While Preserving Privacy. International Journal of Emerging Research in Engineering and Technology, 3(2), 79-88. https://doi.org/10.63282/3050-922X.IJERET-V3I2P109
49. 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
50. Anasuri, S. (2022). Next-Gen DNS and Security Challenges in IoT Ecosystems. International Journal of Emerging Research in Engineering and Technology, 3(2), 89-98. https://doi.org/10.63282/3050-922X.IJERET-V3I2P110
51. Pedda Muntala, P. S. R. (2022). Detecting and Preventing Fraud in Oracle Cloud ERP Financials with Machine Learning. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 3(4), 57-67. https://doi.org/10.63282/3050-9262.IJAIDSML-V3I4P107
52. 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
53. 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
54. Rusum, G. P., & Pappula, K. K. (2023). Low-Code and No-Code Evolution: Empowering Domain Experts with Declarative AI Interfaces. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 4(2), 105-112. https://doi.org/10.63282/3050-9262.IJAIDSML-V4I2P112
55. 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
56. Anasuri, S. (2023). Confidential Computing Using Trusted Execution Environments. International Journal of AI, BigData, Computational and Management Studies, 4(2), 97-110. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V4I2P111
57. Pedda Muntala, P. S. R., & Jangam, S. K. (2023). Context-Aware AI Assistants in Oracle Fusion ERP for Real-Time Decision Support. International Journal of Emerging Trends in Computer Science and Information Technology, 4(1), 75-84. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I1P109
58. 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
59. Enjam, G. R. (2023). AI Governance in Regulated Cloud-Native Insurance Platforms. International Journal of AI, BigData, Computational and Management Studies, 4(3), 102-111. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V4I3P111
60. 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
61. 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
62. Pedda Muntala, P. S. R., & Jangam, S. K. (2021). Real-time Decision-Making in Fusion ERP Using Streaming Data and AI. International Journal of Emerging Research in Engineering and Technology, 2(2), 55-63. https://doi.org/10.63282/3050-922X.IJERET-V2I2P108
63. 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
64. 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
65. 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
66. 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
67. Anasuri, S. (2022). Zero-Trust Architectures for Multi-Cloud Environments. International Journal of Emerging Trends in Computer Science and Information Technology, 3(4), 64-76. https://doi.org/10.63282/3050-9246.IJETCSIT-V3I4P107
68. Pedda Muntala, P. S. R., & Karri, N. (2022). Using Oracle Fusion Analytics Warehouse (FAW) and ML to Improve KPI Visibility and Business Outcomes. International Journal of AI, BigData, Computational and Management Studies, 3(1), 79-88. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V3I1P109
69. 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
70. 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
71. Rusum, G. P. (2023). Large Language Models in IDEs: Context-Aware Coding, Refactoring, and Documentation. International Journal of Emerging Trends in Computer Science and Information Technology, 4(2), 101-110. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I2P110
72. 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
73. Anasuri, S., & Pappula, K. K. (2023). Green HPC: Carbon-Aware Scheduling in Cloud Data Centers. International Journal of Emerging Research in Engineering and Technology, 4(2), 106-114. https://doi.org/10.63282/3050-922X.IJERET-V4I2P111
74. Reddy Pedda Muntala , P. S. (2023). Process Automation in Oracle Fusion Cloud Using AI Agents. International Journal of Emerging Research in Engineering and Technology, 4(4), 112-119. https://doi.org/10.63282/3050-922X.IJERET-V4I4P111
75. 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
76. 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
77. 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
78. 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
79. 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
80. Pedda Muntala, P. S. R. (2022). Enhancing Financial Close with ML: Oracle Fusion Cloud Financials Case Study. International Journal of AI, BigData, Computational and Management Studies, 3(3), 62-69. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V3I3P108
81. 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
82. 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
83. Reddy Pedda Muntala, P. S., & Karri, N. (2023). Voice-Enabled ERP: Integrating Oracle Digital Assistant with Fusion ERP for Hands-Free Operations. International Journal of Emerging Trends in Computer Science and Information Technology, 4(2), 111-120. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I2P111
84. 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
85. 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