Heat Behind the Meter: A Hidden Threat of Thermal Attacks in Edge Colocation Data Centers
Zhihui Shao, Mohammad A. Islam, Shaolei Ren
Abstract
The widespread adoption of Internet of Things and latency-critical applications has fueled the burgeoning development of edge colocation data centers (a.k. a., edge colocation) — small-scale data centers in distributed locations. In an edge colocation, multiple entities/tenants house their own physical servers together, sharing the power and cooling infrastructures for cost efficiency and scalability. In this paper, we discover that the sharing of cooling systems also exposes edge colocations’ potential vulnerabilities to cooling load injection attacks (called thermal attacks) by an attacker which, if left at large, may create thermal emergencies and even trigger system outages. Importantly, thermal attacks can be launched by leveraging the emerging architecture of built-in batteries integrated with servers that can conceal the attacker’s actual server power (or cooling load). We consider both one-shot attacks (which aim at creating system outages) and repeated attacks (which aim at causing frequent thermal emergencies). For repeated attacks, we present a foresighted attack strategy which, using reinforcement learning, learns on the fly a good timing for attacks based on the battery state and benign tenants’ load. We also combine prototype experiments with simulations to validate our attacks and show that, for a small 8kW edge colocation, an attacker can potentially cause significant losses. Finally, we suggest effective countermeasures to the potential threat of thermal attacks.
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