Cite this article
Integrating Anomaly Detection into DevSecOps Pipelines for Continuous Cloud Security
DOI: 10.64180/ijef.412604
BibTeX
@article{vol4issue1integratinganomalydetectionintodevsecopspipelinesforcontinuouscloudsecurity,
title = {Integrating Anomaly Detection into DevSecOps Pipelines for Continuous Cloud Security},
author = {Sidiropoulos, Harry},
journal = {International Journal of Engineering Fields},
volume = {4},
number = {1},
pages = {35--42},
doi = {10.64180/ijef.412604},
issn = {3078-4425}
}
RIS
TY - JOUR AU - Sidiropoulos, Harry TI - Integrating Anomaly Detection into DevSecOps Pipelines for Continuous Cloud Security JO - International Journal of Engineering Fields VL - 4 IS - 1 SP - 35 EP - 42 DO - 10.64180/ijef.412604 AB - <p style="text-align:justify;">The integration of anomaly detection into DevSecOps pipelines represents a paradigm shift in continuous cloud security, moving beyond static vulnerabilities to identify dynamic runtime threats. As cloud-native architectures expand, the traditional security gates in Continuous Integration and Continuous Deployment (CI/CD) pipelines often fail to detect sophisticated, zero-day attacks or nuanced behavioral anomalies. This paper explores the design, deployment, and evaluation of an AI-driven anomaly detection framework embedded directly within DevSecOps workflows. By leveraging unsupervised machine learning algorithms, the proposed framework continuously monitors pipeline telemetry, code commits, and runtime behaviors to flag deviations from established baselines.</p> KW - Anomaly Detection KW - DevSecOps KW - Pipelines KW - Cloud KW - Security SN - 3078-4425 UR - https://journalofengineering.org/article/vol-4-issue-1-integrating-anomaly-detection-into-devsecops-pipelines-for-continuous-cloud-security ER -