一句话：提出 PAFL，将单模式模糊测试优化扩展到工业并行模式，以在多个模糊器实例并行运行时保持效率提升。
现有研究提出了大量提升模糊测试效率的优化策略，但这些策略大多在单模式（仅实例化一个 fuzzer 实例）下设计并验证，能够在各自目标上取得良好效果。然而在实际工业实践中，模糊测试通常以并行模式运行，即同时实例化多个 fuzzer 实例，此时原有单模式优化往往无法保持其效率提升，导致优化收益在真实部署中丢失。针对这一问题，论文提出 PAFL，旨在将单模式下的模糊测试优化扩展到工业并行模式，使并行运行的多实例场景也能继承或维持这些优化的效率优势。摘要主要强调了问题动机与 PAFL 的目标，未展开具体技术机制和实验数据。
Researchers have proposed many optimizations to improve the efficiency of fuzzing, and most optimized strategies work very well on their targets when running in single mode with instantiating one fuzzer instance. However, in real industrial practice, most fuzzers run in parallel mode with instantiating multiple fuzzer instances, and those optimizations unfortunately fail to maintain the efficiency improvements.
DOI 原文 ·
@inproceedings{paperbot4625,
title = {PAFL: extend fuzzing optimizations of single mode to industrial parallel mode},
author = {Jie Liang and Yu Jiang and Yuanliang Chen and Mingzhe Wang and Chijin Zhou and Jiaguang Sun},
booktitle = {FSE},
year = {2018},
doi = {10.1145/3236024.3275525}
}