Yonghao Zou (Beihang University and Peking University), Jia-Ju Bai (Beihang University), Zu-Ming Jiang (ETH Zurich), Ming Zhao (Arizona State University), Diyu Zhou (Peking University)

This paper presents DistFuzz, which, to our knowledge, is the first feedback-guided blackbox fuzzing framework for distributed systems. The novelty of DistFuzz comes from two conceptual contributions on key aspects of distributed system fuzzing: the input space and feedback metrics. Specifically, unlike prior work that focuses on systematically mutating faults, exploiting the request-driven and timing-dependence nature of distributed systems, DistFuzz proposes a multi-dimensional input space by incorporating regular events and relative timing among events as the other two dimensions. Furthermore, observing that important state changes in distributed systems can be indicated by network messages among nodes, DistFuzz utilizes the sequences of network messages with symmetry-based pruning as program feedback, which departs from the conventional wisdom that effective feedback requires code instrumentation/analysis and/or user inputs. DistFuzz finds 52 real bugs in ten popular distributed systems in C/C++, Go, and Java. Among these bugs, 28 have been confirmed by the developers, 20 were unknown before, and 4 have been assigned with CVEs.

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Revisiting EM-based Estimation for Locally Differentially Private Protocols

Yutong Ye (Institute of software, Chinese Academy of Sciences & Zhongguancun Laboratory, Beijing, PR.China.), Tianhao Wang (University of Virginia), Min Zhang (Institute of Software, Chinese Academy of Sciences), Dengguo Feng (Institute of Software, Chinese Academy of Sciences)

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Crosstalk-induced Side Channel Threats in Multi-Tenant NISQ Computers

Ruixuan Li (Choudhury), Chaithanya Naik Mude (University of Wisconsin-Madison), Sanjay Das (The University of Texas at Dallas), Preetham Chandra Tikkireddi (University of Wisconsin-Madison), Swamit Tannu (University of Wisconsin, Madison), Kanad Basu (University of Texas at Dallas)

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GAP-Diff: Protecting JPEG-Compressed Images from Diffusion-based Facial Customization

Haotian Zhu (Nanjing University of Science and Technology), Shuchao Pang (Nanjing University of Science and Technology), Zhigang Lu (Western Sydney University), Yongbin Zhou (Nanjing University of Science and Technology), Minhui Xue (CSIRO's Data61)

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