SECURING CLOUD-BASED STREAMING DATA PLATFORMS: BEST PRACTICES AND FRAMEWORKS

Cloud-based streaming data platforms have become foundational to modern enterprises that rely on real-time insights, from financial services monitoring to connected retail operations.As organizations move critical data pipelines into the cloud, the attack surface for adversaries expands considerably.This article examines security challenges in streaming data architectures and presents a framework of best practices for protecting sensitive data in transit, at rest, and during processing.Key strategies include end-to-end encryption, automated vulnerability scanning, identity and access management (IAM) hardening, and continuous compliance validation.Industry implementations and case studies highlight measurable outcomes such as reduced incident rates, improved compliance adherence, and enhanced resilience of streaming analytics systems.The goal is to provide technology leaders with a comprehensive set of practices to secure cloud-based streaming data platforms while enabling innovation and agility.

Publication Details

Journal
International Research Journal of Modernization in Engineering Technology and Science
Published
2025-09-05
DOI
https://doi.org/10.56726/irjmets17179
Primary Topic
Privacy-Preserving Technologies in Data
Type
article
Field-Weighted Citation Impact
0.00
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article

SECURING CLOUD-BASED STREAMING DATA PLATFORMS: BEST PRACTICES AND FRAMEWORKS

International Research Journal of Modernization in Engineering Technology and Science
Privacy-Preserving Technologies in Data
article

SECURING CLOUD-BASED STREAMING DATA PLATFORMS: BEST PRACTICES AND FRAMEWORKS

article en

Abstract

Cloud-based streaming data platforms have become foundational to modern enterprises that rely on real-time insights, from financial services monitoring to connected retail operations.As organizations move critical data pipelines into the cloud, the attack surface for adversaries expands considerably.This article examines security challenges in streaming data architectures and presents a framework of best practices for protecting sensitive data in transit, at rest, and during processing.Key strategies include end-to-end encryption, automated vulnerability scanning, identity and access management (IAM) hardening, and continuous compliance validation.Industry implementations and case studies highlight measurable outcomes such as reduced incident rates, improved compliance adherence, and enhanced resilience of streaming analytics systems.The goal is to provide technology leaders with a comprehensive set of practices to secure cloud-based streaming data platforms while enabling innovation and agility.

International Research Journal of Modernization in Engineering Technology and Science
Openalex Percentile: Top 88%
Privacy-Preserving Technologies in Data
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