International Journal For Multidisciplinary Research

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Crucial role of automation for platform and infrastructure level monitoring for BCSI repositories

Author(s) Suchismita Chatterjee
Country United States
Abstract Bulk Electric System Cyber System Information (BCSI) repositories play a pivotal role in the energy sector by safeguarding critical data that supports the secure and reliable operation of electric grids. Monitoring the platform and infrastructure layers of these repositories is essential to ensure their security, availability, and compliance with stringent regulatory requirements like NERC CIP standards. Traditional manual monitoring approaches are insufficient to handle the complexities and evolving threats in these environments.
This paper explores the crucial role of automation in enhancing platform and infrastructure-level monitoring for BCSI repositories. It highlights how automated tools and technologies enable real-time monitoring, anomaly detection, and proactive risk mitigation while reducing human errors and operational inefficiencies. Additionally, it examines the alignment of automated monitoring practices with compliance mandates, ensuring audit readiness and regulatory adherence.
By addressing challenges such as cost, integration with legacy systems, and workforce readiness, the paper underscores the transformative potential of automation in strengthening the security and resilience of BCSI repositories. The conclusion emphasizes best practices and emerging trends, advocating for the adoption of advanced automation strategies to meet the demands of the modern utility landscape.
Keywords Orca Security, Cloud-based SIEM, Zabbix, SolarWinds, Cisco pyATS, FedRAMP, cloud infrastructure security, automation, monitoring tools, continuous monitoring, cybersecurity incident response, machine learning, data analytics, infrastructure monitoring, network automation, Python-based framework, customizable alerts, open-source tools, security compliance, cloud environments, government agencies, infrastructure optimization.
Field Computer > Data / Information
Published In Volume 2, Issue 6, November-December 2020
Published On 2020-11-08
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E-ISSN 2582-2160
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