Identity and Access Management (IAM): Strengthening Security inHybrid Work Environments

Authors

  • Sabeeruddin Shaik (Independent Researcher) Portland, Oregon, US Author

DOI:

https://doi.org/10.47363/JAICC/2024(3)E248

Keywords:

Identity and Access Management (IAM), Hybrid Work, Security, Zero Trust, Access Control, Cybersecurity, Compliance, Blockchain, Ai, Biometric Authentication

Abstract

The swift implementation of hybrid work settings has altered organizational functions, introducing distinct security problems. Identity and Access Management (IAM) has become an essential framework for safeguarding digital assets while facilitating easy access for a distributed workforce. This article examines the relevance of IAM in hybrid work environments, highlighting its importance in threat mitigation, user experience enhancement, and compliance assurance. This paper provides a comprehensive examination of IAM solutions, detailing their applications, effects, problems, and future potential while proposing techniques to enhance security and flexibility in changing work contexts. Furthermore, it explores new innovations, governance, identity lifecycle management, risk assessment frameworks, and implementation considerations, establishing IAM as a fundamental element for hybrid work security. The document encompasses a comprehensive examination of case studies, practical implementation challenges, and emerging technologies including blockchain and quantum computing. It also assesses IAM maturity models and the ethical implications of managing sensitive identification
information. Identity and Access Management (IAM) is positioned as a crucial facilitator for enterprises to maintain resilience and compliance in the context of hybrid work.

Author Biography

  • Sabeeruddin Shaik, (Independent Researcher) Portland, Oregon, US

    Sabeeruddin Shaik, (Independent Researcher) Portland, Oregon, US. 

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Published

2024-10-29

How to Cite

Identity and Access Management (IAM): Strengthening Security inHybrid Work Environments. (2024). Journal of Artificial Intelligence & Cloud Computing, 3(5), 1-3. https://doi.org/10.47363/JAICC/2024(3)E248

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