PREVENTING INSIDER THREATS IN CLOUD ENVIRONMENTS: ANOMALY DETECTION AND BEHAVIORAL ANALYSIS APPROACHES

Journal of Science Technology and Research (JSTAR) 3 (1):225-232 (2022)
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Abstract

Insider threats pose a significant risk to cloud environments, where traditional security measures may fall short. This manuscript delves into the use of anomaly detection and behavioral analysis to mitigate these risks. We explore the unique challenges of cloud security, examine current methodologies, and provide practical insights into implementing effective insider threat detection mechanisms. By integrating these advanced techniques, organizations can enhance their security posture and protect sensitive data in the cloud. In today's digital age, the fusion of cybersecurity and network architecture is paramount to building a resilient and secure IT infrastructure. This manuscript explores the critical interdependence between these two domains, emphasizing the need for an integrated approach to safeguard against ever-evolving cyber threats. By examining current trends, challenges, and best practices, we aim to provide a comprehensive guide for organizations to enhance their cybersecurity posture through robust network architecture design. Key words: :

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