Fan Sang (Georgia Institute of Technology), Jaehyuk Lee (Georgia Institute of Technology), Xiaokuan Zhang (George Mason University), Meng Xu (University of Waterloo), Scott Constable (Intel), Yuan Xiao (Intel), Michael Steiner (Intel), Mona Vij (Intel), Taesoo Kim (Georgia Institute of Technology)

Effectively mitigating side-channel attacks (SCAs) in Trusted Execution Environments (TEEs) remains challenging despite advances in existing defenses. Current detection-based defenses hinge on observing abnormal victim performance characteristics but struggle to detect attacks leaking smaller portions of the secret across multiple executions. Limitations of existing detection-based defenses stem from various factors, including the absence of a trusted microarchitectural data source in TEEs, low-quality available data, inflexibility of victim responses, and platform-specific constraints. We contend that the primary obstacles to effective detection techniques can be attributed to the lack of direct access to precise microarchitectural information within TEEs.

We propose SENSE, a solution that actively exposes underlying microarchitectural information to userspace TEEs. SENSE enables userspace software in TEEs to subscribe to fine-grained microarchitectural events and utilize the events as a means to contextualize the ongoing microarchitectural states. We initially demonstrate SENSE’s capability by applying it to defeat the state-of-the-art cache-based side-channel attacks. We conduct a comprehensive security analysis to ensure that SENSE does not leak more information than a system without it does. We prototype SENSE on a gem5-based emulator, and our evaluation shows that SENSE is secure, can effectively defeats cache SCAs, and incurs negligible performance overhead (1.2%) under benign situations.

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Raushan Kumar Singh (IIT Ropar), Sudeepta Mishra (IIT Ropar)

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Wenjun Zhu (Zhejiang University), Yuan Sun (Zhejiang University), Jiani Liu (Zhejiang University), Yushi Cheng (Zhejiang University), Xiaoyu Ji (Zhejiang University), Wenyuan Xu (Zhejiang University)

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Shaofei Li (Key Laboratory of High-Confidence Software Technologies (MOE), School of Computer Science, Peking University), Feng Dong (Huazhong University of Science and Technology), Xusheng Xiao (Arizona State University), Haoyu Wang (Huazhong University of Science and Technology), Fei Shao (Case Western Reserve University), Jiedong Chen (Sangfor Technologies Inc.), Yao Guo (Key Laboratory of High-Confidence Software Technologies…

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Hexuan Yu (Virginia Polytechnic Institute and State University), Changlai Du (Virginia Polytechnic Institute and State University), Yang Xiao (University of Kentucky), Angelos Keromytis (Georgia Institute of Technology), Chonggang Wang (InterDigital), Robert Gazda (InterDigital), Y. Thomas Hou (Virginia Polytechnic Institute and State University), Wenjing Lou (Virginia Polytechnic Institute and State University)

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