Maryam Rostamipoor (Stony Brook University), Seyedhamed Ghavamnia (University of Connecticut), Michalis Polychronakis (Stony Brook University)

As the use of language-level sandboxing for running untrusted code grows, the risks associated with memory disclosure vulnerabilities and transient execution attacks become increasingly significant. Besides the execution of untrusted JavaScript or WebAssembly code in web browsers, serverless environments have also started relying on language-level isolation to improve scalability by running multiple functions from different customers within a single process. Web browsers have adopted process-level sandboxing to mitigate memory leakage attacks, but this solution is not applicable in serverless environments, as running each function as a separate process would negate the performance benefits of language-level isolation.

In this paper we present LeakLess, a selective data protection approach for serverless computing platforms. LeakLess alleviates the limitations of previous selective data protection techniques by combining in-memory encryption with a separate I/O module to enable the safe transmission of the protected data between serverless functions and external hosts. We implemented LeakLess on top of the Spin serverless platform, and evaluated it with real-world serverless applications. Our results demonstrate that LeakLess offers robust protection while incurring a minor throughput decrease under stress-testing conditions of up to 2.8% when the I/O module runs on a different host than the Spin runtime, and up to 8.5% when it runs on the same host.

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Siniel: Distributed Privacy-Preserving zkSNARK

Yunbo Yang (The State Key Laboratory of Blockchain and Data Security, Zhejiang University), Yuejia Cheng (Shanghai DeCareer Consulting Co., Ltd), Kailun Wang (Beijing Jiaotong University), Xiaoguo Li (College of Computer Science, Chongqing University), Jianfei Sun (School of Computing and Information Systems, Singapore Management University), Jiachen Shen (Shanghai Key Laboratory of Trustworthy Computing, East China Normal…

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EMIRIS: Eavesdropping on Iris Information via Electromagnetic Side Channel

Wenhao Li (Shandong University), Jiahao Wang (Shandong University), Guoming Zhang (Shandong University), Yanni Yang (Shandong University), Riccardo Spolaor (Shandong University), Xiuzhen Cheng (Shandong University), Pengfei Hu (Shandong University)

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Tweezers: A Framework for Security Event Detection via Event...

Jian Cui (Indiana University), Hanna Kim (KAIST), Eugene Jang (S2W Inc.), Dayeon Yim (S2W Inc.), Kicheol Kim (S2W Inc.), Yongjae Lee (S2W Inc.), Jin-Woo Chung (S2W Inc.), Seungwon Shin (KAIST), Xiaojing Liao (Indiana University)

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BARBIE: Robust Backdoor Detection Based on Latent Separability

Hanlei Zhang (Zhejiang University), Yijie Bai (Zhejiang University), Yanjiao Chen (Zhejiang University), Zhongming Ma (Zhejiang University), Wenyuan Xu (Zhejiang University)

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