IOLeak: Side-channel Information Leakage by Monitoring CPU Frequency Scaling through I/Os

Power efficiency gains increasing importance to both general-purpose and embedded computing systems. CPU frequency scaling is widely used to dynamically adjust the speed and voltage of CPU cores in real time, aiming to gain both high performance and power efficiency. Prior works indicate that the runtime variations of CPU frequency expose a viable attack surface to leak information of the ongoing workload. In this paper, we find that the performance of I/O requests, such as file I/Os on a fast storage device, is affected by the runtime changes of CPU frequency and, in turn, is exploitable to speculate the workload’s sensitive information. We are hence motivated to develop IOLeak , a new side channel that is based on CPU frequency scaling but does not directly rely on CPU frequency values. We first build IOLeak covert channel by online monitoring I/O latency for secretive communication, both in noise-free and noisy environments. Next, we leverage IOLeak to launch a number of stealthy attacks, such as extracting cryptographic keys and fingerprinting websites, and confirm that IOLeak successfully leaks information by conducting inconspicuous file I/O operations. We particularly demonstrate that IOLeak is effective in the cross-virtual machine (VM) fashion that has not been covered by prior attacks relying on CPU frequency values. We also verify that IOLeak is capable in both general-purpose computers and embedded systems. These justify the serious security breach that IOLeak causes. Regarding the impact of IOLeak, we have responsibly reported our findings to the security teams of relevant organizations and received their feedback.

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Publication Details

Journal
ACM Transactions on Embedded Computing Systems
Published
2026-07-16
DOI
https://doi.org/10.1145/3830017
Primary Topic
Security and Verification in Computing
Type
article
Field-Weighted Citation Impact
0.00
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article

IOLeak: Side-channel Information Leakage by Monitoring CPU Frequency Scaling through I/Os

Siting Liu, Chundong Wang, Li Zhu
ACM Transactions on Embedded Computing Systems
Security and Verification in Computing
article

IOLeak: Side-channel Information Leakage by Monitoring CPU Frequency Scaling through I/Os

Siting Liu, Chundong Wang, Li Zhu
article en

Abstract

Power efficiency gains increasing importance to both general-purpose and embedded computing systems. CPU frequency scaling is widely used to dynamically adjust the speed and voltage of CPU cores in real time, aiming to gain both high performance and power efficiency. Prior works indicate that the runtime variations of CPU frequency expose a viable attack surface to leak information of the ongoing workload. In this paper, we find that the performance of I/O requests, such as file I/Os on a fast storage device, is affected by the runtime changes of CPU frequency and, in turn, is exploitable to speculate the workload’s sensitive information. We are hence motivated to develop IOLeak , a new side channel that is based on CPU frequency scaling but does not directly rely on CPU frequency values. We first build IOLeak covert channel by online monitoring I/O latency for secretive communication, both in noise-free and noisy environments. Next, we leverage IOLeak to launch a number of stealthy attacks, such as extracting cryptographic keys and fingerprinting websites, and confirm that IOLeak successfully leaks information by conducting inconspicuous file I/O operations. We particularly demonstrate that IOLeak is effective in the cross-virtual machine (VM) fashion that has not been covered by prior attacks relying on CPU frequency values. We also verify that IOLeak is capable in both general-purpose computers and embedded systems. These justify the serious security breach that IOLeak causes. Regarding the impact of IOLeak, we have responsibly reported our findings to the security teams of relevant organizations and received their feedback.

ACM Transactions on Embedded Computing Systems
ShanghaiTech University (CN)
Affordable and clean energy
Openalex Percentile: Top 6%
Security and Verification in Computing
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