Thermal Management in Large Data Centers: Security Threats and Mitigation
This addresses security vulnerabilities in large data centers for cloud and IoT services, but it is incremental as it builds on existing thermal anomaly detection methods.
The paper tackles the problem of thermal attacks on data center cooling systems, which can cause meltdowns, by analyzing threats and proposing a hybrid method with multi-variant anomaly detection and a fuzzy-based health factor to enhance security.
Data centres are experiencing significant growth in their scale, especially, with the ever-increasing demand for cloud and IoT services. However, this rapid growth has raised numerous security issues and vulnerabilities; new types of strategic cyber-attacks are aimed at specific physical components of data centres that keep them operating. Attacks against temperature monitoring and cooling systems of data centres, also known as thermal attacks, can cause a complete meltdown and are generally considered difficult to address. In this paper, we focus on this issue by analysing the potential security threats to these systems and their impact on the overall data center safety and performance. We also present current thermal anomaly detection methods and their limitations. Finally, we propose a hybrid method that uses multi-variant anomaly detection to prevent thermal attacks, as well as a fuzzy-based health factor to enhance data center thermal awareness and security