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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Secure IP Address Allocation at Cloud Scale

Eric Pauley (University of Wisconsin–Madison), Kyle Domico (University of Wisconsin–Madison), Blaine Hoak (University of Wisconsin–Madison), Ryan Sheatsley (University of Wisconsin–Madison), Quinn Burke (University of Wisconsin–Madison), Yohan Beugin (University of Wisconsin–Madison), Engin Kirda (Northeastern University), Patrick McDaniel (University of Wisconsin–Madison)

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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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A Method to Facilitate Membership Inference Attacks in Deep...

Zitao Chen (University of British Columbia), Karthik Pattabiraman (University of British Columbia)

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PBP: Post-training Backdoor Purification for Malware Classifiers

Dung Thuy Nguyen (Vanderbilt University), Ngoc N. Tran (Vanderbilt University), Taylor T. Johnson (Vanderbilt University), Kevin Leach (Vanderbilt University)

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