Weili Wang (Southern University of Science and Technology), Honghan Ji (ByteDance Inc.), Peixuan He (ByteDance Inc.), Yao Zhang (ByteDance Inc.), Ye Wu (ByteDance Inc.), Yinqian Zhang (Southern University of Science and Technology)

The advancement of trusted execution environments (TEEs) has enabled the confidential computing paradigm and created new application scenarios for WebAssembly (Wasm). "Wasm+TEE" designs achieve in-enclave multi-tenancy with strong isolation, facilitating concurrent execution of untrusted code instances from multiple users. However, the linear memory model of Wasm lacks efficient cross-module data sharing and fine-grained memory access control, significantly restricting its applications in certain confidential computing scenarios where secure data sharing is essential (e.g., confidential stateful FaaS and data marketplaces). In this paper, we propose WAVEN (WebAssembly Memory Virtualization for ENclaves), a novel WebAssembly memory virtualization scheme, to enable memory sharing among Wasm modules and page-level access control. We implement WAVEN atop WAMR, a popular Wasm runtime for TEEs, and empirically demonstrate its efficiency and effectiveness. To the best of our knowledge, our work represents the first approach that enables cross-module memory sharing with fine-grained memory access control in Wasm.

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SIGuard: Guarding Secure Inference with Post Data Privacy

Xinqian Wang (RMIT University), Xiaoning Liu (RMIT University), Shangqi Lai (CSIRO Data61), Xun Yi (RMIT University), Xingliang Yuan (University of Melbourne)

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RContainer: A Secure Container Architecture through Extending ARM CCA...

Qihang Zhou (Institute of Information Engineering, Chinese Academy of Sciences), Wenzhuo Cao (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyberspace Security, University of Chinese Academy of Sciences), Xiaoqi Jia (Institute of Information Engineering, Chinese Academy of Sciences), Peng Liu (The Pennsylvania State University, USA), Shengzhi Zhang (Department of Computer Science, Metropolitan College,…

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Defending Against Membership Inference Attacks on Iteratively Pruned Deep...

Jing Shang (Beijing Jiaotong University), Jian Wang (Beijing Jiaotong University), Kailun Wang (Beijing Jiaotong University), Jiqiang Liu (Beijing Jiaotong University), Nan Jiang (Beijing University of Technology), Md Armanuzzaman (Northeastern University), Ziming Zhao (Northeastern University)

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On the Realism of LiDAR Spoofing Attacks against Autonomous...

Takami Sato (University of California, Irvine), Ryo Suzuki (Keio University), Yuki Hayakawa (Keio University), Kazuma Ikeda (Keio University), Ozora Sako (Keio University), Rokuto Nagata (Keio University), Ryo Yoshida (Keio University), Qi Alfred Chen (University of California, Irvine), Kentaro Yoshioka (Keio University)

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