Dongwei Xiao (The Hong Kong University of Science and Technology), Zhibo Liu (The Hong Kong University of Science and Technology), Yiteng Peng (The Hong Kong University of Science and Technology), Shuai Wang (The Hong Kong University of Science and Technology)

Zero-knowledge (ZK) proofs have been increasingly popular in privacy-preserving applications and blockchain systems. To facilitate handy and efficient ZK proof generation for normal users, the industry has designed domain-specific languages (DSLs) and ZK compilers. Given a program in ZK DSL, a ZK compiler compiles it into a circuit, which is then passed to the prover and verifier for ZK checking. However, the correctness of ZK compilers is not well studied, and recent works have shown that de facto ZK compilers are buggy, which can allow malicious users to generate invalid proofs that are accepted by the verifier, causing security breaches and financial losses in cryptocurrency.

In this paper, we propose MTZK, a metamorphic testing framework to test ZK compilers and uncover incorrect compilations. Our approach leverages deliberately designed metamorphic relations (MRs) to mutate ZK compiler inputs. This way, ZK compilers can be automatically tested for compilation correctness using inputs and mutated variants. We propose a set of design considerations and optimizations to deliver an efficient and effective testing framework. In the evaluation of four industrial ZK compilers, we successfully uncovered 21 bugs, out of which the developers have promptly patched 15. We also show possible exploitations of the uncovered bugs to demonstrate their severe security implications.

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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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Secure Data Analytics in Apache Spark with Fine-grained Policy...

Byeongwook Kim (Seoul National University), Jaewon Hur (Seoul National University), Adil Ahmad (Arizona State University), Byoungyoung Lee (Seoul National University)

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Feedback-Guided API Fuzzing of 5G Network

Tianchang Yang (Pennsylvania State University), Sathiyajith K S (Pennsylvania State University), Ashwin Senthil Arumugam (Pennsylvania State University), Syed Rafiul Hussain (Pennsylvania State University)

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Delay-allowed Differentially Private Data Stream Release

Xiaochen Li (University of Virginia), Zhan Qin (Zhejiang University), Kui Ren (Zhejiang University), Chen Gong (University of Virginia), Shuya Feng (University of Connecticut), Yuan Hong (University of Connecticut), Tianhao Wang (University of Virginia)

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