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Learn about advanced optimization techniques for kernel fuzzing through this 18-minute conference presentation from USENIX ATC '25. Discover how researchers from East China Normal University, ETH Zurich, and The Chinese University of Hong Kong address the critical bottleneck of input minimization in coverage-guided kernel fuzzing, which consumes over half of fuzzing resources and significantly limits effectiveness. Explore two novel optimization strategies: influence-guided call removal and type-informed argument simplification, both designed to reduce the number of dynamic program executions required for coverage verification. Examine the implementation of these strategies in SyzMini, an optimized version of Syzkaller, the most popular kernel fuzzer, and understand how it achieves a 60.7% reduction in minimization cost while improving branch coverage by 12.5% and discovering 1.7-2X more unique bugs. Review the practical impact of this research, including the discovery of 13 previously unknown bugs in the latest upstream kernel version, with four already fixed, and learn about the general applicability of these optimization strategies for enhancing other kernel fuzzers.
