How to implement a Zero Trust architecture for your organization using IAM

Authors

  • Sairamesh Konidala Vice President at JPMorgan & Chase, USA Author
  • Jeevan Manda Project Manager at Metanoia Solutions Inc, USA Author

Keywords:

Zero Trust Architecture, Identity and Access Management (IAM)

Abstract

Abstract:
Implementing a zero-trust architecture through Identity and Access Management (IAM) is becoming essential for organizations aiming to bolster their cybersecurity frameworks. Traditional perimeter-based security models are no longer adequate in today’s remote work environment, cloud adoption, and sophisticated cyber threats. Zero Trust shifts the focus from network-centric to user and device-centric security, where no entity, internal or external, is trusted by default. IAM plays a crucial role in this model, enabling organizations to authenticate and authorize access based on user identity, device health, and other context-driven parameters. By integrating IAM solutions, businesses can enforce the principles of Zero Trust, such as “never trust, always verify,” to ensure only the right people and devices have access to the right resources. This approach involves several key steps, including multi-factor authentication, least privilege access, continuous monitoring, and dynamic policy enforcement. These elements allow organizations to minimize risk by limiting access and continuously validating trustworthiness across all access points. Implementing Zero Trust with IAM strengthens security and streamlines compliance and audit processes, making it easier to adhere to regulatory standards. For organizations looking to adopt this architecture, understanding the synergy between IAM and Zero Trust is vital for building a resilient security strategy that can adapt to emerging threats. This approach empowers security teams to proactively respond to suspicious activities and potential breaches, creating a secure and adaptive environment that safeguards valuable data and resources without compromising productivity.

Downloads

Download data is not yet available.

References

DeCusatis, C., Liengtiraphan, P., Sager, A., & Pinelli, M. (2016, November). Implementing zero trust cloud networks with transport access control and first packet authentication. In 2016 IEEE International Conference on Smart Cloud (SmartCloud) (pp. 5-10). IEEE.

DeCusatis, C., Liengtiraphan, P., Sager, A., & Pinelli, M. (2016, November). Implementing zero trust cloud networks with transport access control and first packet authentication. In 2016 IEEE International Conference on Smart Cloud (SmartCloud) (pp. 5-10). IEEE.

Indu, I., Anand, P. R., & Bhaskar, V. (2018). Identity and access management in cloud environment: Mechanisms and challenges. Engineering science and technology, an international journal, 21(4), 574-588.

Bradford, M., Earp, J. B., & Grabski, S. (2014). Centralized end-to-end identity and access management and ERP systems: A multi-case analysis using the Technology Organization Environment framework. International Journal of Accounting Information Systems, 15(2), 149-165.

Gonzales, D., Kaplan, J. M., Saltzman, E., Winkelman, Z., & Woods, D. (2015). Cloud-trust—A security assessment model for infrastructure as a service (IaaS) clouds. IEEE Transactions on Cloud Computing, 5(3), 523-536.

Mohammed, I. A. (2013). Intelligent authentication for identity and access management: a review paper. International Journal of Managment, IT and Engineering (IJMIE), 3(1), 696-705.

Syed, F. M., & ES, F. K. (2018). The Role of IAM in Mitigating Ransomware Attacks on Healthcare Facilities. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 9(1), 121-154.

Cunningham, C., Blankenship, J., Balaouras, S., Murphy, R., & Cyr, M. (2018). The zero trust eXtended (ZTX) ecosystem. Forrester, Cambridge, MA.

Almulla, S. A., & Yeun, C. Y. (2010, March). Cloud computing security management. In 2010 Second International Conference on Engineering System Management and Applications (pp. 1-7). IEEE.

Kuperberg, M. (2019). Blockchain-based identity management: A survey from the enterprise and ecosystem perspective. IEEE Transactions on Engineering Management, 67(4), 1008-1027.

Mikula, T., & Jacobsen, R. H. (2018, August). Identity and access management with blockchain in electronic healthcare records. In 2018 21st Euromicro conference on digital system design (DSD) (pp. 699-706). IEEE.

Nadareishvili, I., Mitra, R., McLarty, M., & Amundsen, M. (2016). Microservice architecture: aligning principles, practices, and culture. " O'Reilly Media, Inc.".

Ross, J. W., Beath, C. M., & Mocker, M. (2019). Designed for digital: How to architect your business for sustained success. Mit Press.

Erl, T., Puttini, R., & Mahmood, Z. (2013). Cloud computing: concepts, technology & architecture. Pearson Education.

Smari, W. W., Clemente, P., & Lalande, J. F. (2014). An extended attribute based access control model with trust and privacy: Application to a collaborative crisis management system. Future Generation Computer Systems, 31, 147-168.

Gade, K. R. (2019). Data Migration Strategies for Large-Scale Projects in the Cloud for Fintech. Innovative Computer Sciences Journal, 5(1).

Gade, K. R. (2018). Real-Time Analytics: Challenges and Opportunities. Innovative Computer Sciences Journal, 4(1).

Boda, V. V. R., & Immaneni, J. (2019). Streamlining FinTech Operations: The Power of SysOps and Smart Automation. Innovative Computer Sciences Journal, 5(1).

Nookala, G., Gade, K. R., Dulam, N., & Thumburu, S. K. R. (2019). End-to-End Encryption in Enterprise Data Systems: Trends and Implementation Challenges. Innovative Computer Sciences Journal, 5(1).

Katari, A. (2019). Real-Time Data Replication in Fintech: Technologies and Best Practices. Innovative Computer Sciences Journal, 5(1).

Katari, A. (2019). ETL for Real-Time Financial Analytics: Architectures and Challenges. Innovative Computer Sciences Journal, 5(1).

Komandla, V. Enhancing Security and Fraud Prevention in Fintech: Comprehensive Strategies for Secure Online Account Opening.

Komandla, V. Transforming Financial Interactions: Best Practices for Mobile Banking App Design and Functionality to Boost User Engagement and Satisfaction.

Gade, K. R. (2017). Integrations: ETL vs. ELT: Comparative analysis and best practices. Innovative Computer Sciences Journal, 3(1).

Naresh Dulam. DataOps: Streamlining Data Management for Big Data and Analytics . Distributed Learning and Broad Applications in Scientific Research, vol. 2, Oct. 2016, pp. 28-50

Muneer Ahmed Salamkar, and Karthik Allam. Architecting Data Pipelines: Best Practices for Designing Resilient, Scalable, and Efficient Data Pipelines. Distributed Learning and Broad Applications in Scientific Research, vol. 5, Jan. 2019

Muneer Ahmed Salamkar. ETL Vs ELT: A Comprehensive Exploration of Both Methodologies, Including Real-World Applications and Trade-Offs. Distributed Learning and Broad Applications in Scientific Research, vol. 5, Mar. 2019

Muneer Ahmed Salamkar. Next-Generation Data Warehousing: Innovations in Cloud-Native Data Warehouses and the Rise of Serverless Architectures. Distributed Learning and Broad Applications in Scientific Research, vol. 5, Apr. 2019

Muneer Ahmed Salamkar. Real-Time Data Processing: A Deep Dive into Frameworks Like Apache Kafka and Apache Pulsar. Distributed Learning and Broad Applications in Scientific Research, vol. 5, July 2019

Muneer Ahmed Salamkar, and Karthik Allam. “Data Lakes Vs. Data Warehouses: Comparative Analysis on When to Use Each, With Case Studies Illustrating Successful Implementations”. Distributed Learning and Broad Applications in Scientific Research, vol. 5, Sept. 2019

Naresh Dulam. Apache Spark: The Future Beyond MapReduce. Distributed Learning and Broad Applications in Scientific Research, vol. 1, Dec. 2015, pp. 136-5

Naresh Dulam. NoSQL Vs SQL: Which Database Type Is Right for Big Data?. Distributed Learning and Broad Applications in Scientific Research, vol. 1, May 2015, pp. 115-3

Naresh Dulam. Data Lakes: Building Flexible Architectures for Big Data Storage. Distributed Learning and Broad Applications in Scientific Research, vol. 1, Oct. 2015, pp. 95-114

Naresh Dulam. The Rise of Kubernetes: Managing Containers in Distributed Systems. Distributed Learning and Broad Applications in Scientific Research, vol. 1, July 2015, pp. 73-94

Naresh Dulam. Snowflake: A New Era of Cloud Data Warehousing. Distributed Learning and Broad Applications in Scientific Research, vol. 1, Apr. 2015, pp. 49-72

Sarbaree Mishra. A Distributed Training Approach to Scale Deep Learning to Massive Datasets. Distributed Learning and Broad Applications in Scientific Research, vol. 5, Jan. 2019

Sarbaree Mishra, et al. Training Models for the Enterprise - A Privacy Preserving Approach. Distributed Learning and Broad Applications in Scientific Research, vol. 5, Mar. 2019

Sarbaree Mishra. Distributed Data Warehouses - An Alternative Approach to Highly Performant Data Warehouses. Distributed Learning and Broad Applications in Scientific Research, vol. 5, May 2019

Sarbaree Mishra, et al. Improving the ETL Process through Declarative Transformation Languages. Distributed Learning and Broad Applications in Scientific Research, vol. 5, June 2019

Sarbaree Mishra. A Novel Weight Normalization Technique to Improve Generative Adversarial Network Training. Distributed Learning and Broad Applications in Scientific Research, vol. 5, Sept. 2019

Downloads

Published

21-01-2020

How to Cite

[1]
Sairamesh Konidala and Jeevan Manda, “How to implement a Zero Trust architecture for your organization using IAM”, Distrib Learn Broad Appl Sci Res, vol. 6, pp. 1083–1102, Jan. 2020, Accessed: Dec. 29, 2024. [Online]. Available: https://dlabi.org/index.php/journal/article/view/275

Most read articles by the same author(s)

1 2 > >> 

Similar Articles

1-10 of 175

You may also start an advanced similarity search for this article.