| 1 | SHI J, WANG Z, FENG Z, et al. AIFORE: smart fuzzing based on automatic input format reverse engineering [C]// Proceedings of the 32nd USENIX Security Symposium. Berkeley: USENIX Association, 2023: 4967-4984. | 
																													
																						| 2 | ZHANG G, WANG P, YUE T, et al. MobFuzz: adaptive multi-objective optimization in gray-box fuzzing [C]// Proceedings of the 2022 Annual Network and Distributed System Security Symposium. Reston, VA: Internet Society, 2022: 1-18. | 
																													
																						| 3 | SHE D, SHAH A, JANA S. Effective seed scheduling for fuzzing with graph centrality analysis [C]// Proceedings of the 2022 IEEE Symposium on Security and Privacy. Piscataway: IEEE, 2022: 2194-2211. | 
																													
																						| 4 | BUNDT J, FASANO A, DOLAN-GAVITT B, et al. Homo in Machina: improving fuzz testing coverage via compartment analysis[C]// Proceedings of the 2023 IEEE Conference on Software Testing, Verification and Validation. Piscataway: IEEE, 2023: 117-128. | 
																													
																						| 5 | ZALEWSKI M. American fuzzy lop (2.52b) [EB/OL]. [2022-01- 13].. | 
																													
																						| 6 | GAN S, ZHANG C, QIN X, et al. CollAFL: path sensitive fuzzing[C]// Proceedings of the 2018 IEEE Symposium on Security and Privacy. Piscataway: IEEE, 2018: 679-696. | 
																													
																						| 7 | GAN S, ZHANG C, CHEN P, et al. GREYONE: data flow sensitive fuzzing [C]// Proceedings of the 29th USENIX Security Symposium. Berkeley: USENIX Association, 2020: 2577-2594. | 
																													
																						| 8 | NIKOLIĆ I, MANTU R, SHEN S, et al. Refined grey-box fuzzing with SIVO [C]// Proceedings of the 2021 International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment International Conference, LNCS 12756. Cham: Springer, 2021: 106-129. | 
																													
																						| 9 | ASCHERMANN C, SCHUMILO S, BLAZYTKO T, et al. REDQUEEN: fuzzing with input-to-state correspondence[C]// Proceedings of the 2019 Annual Network and Distributed System Security Symposium. Reston, VA: Internet Society, 2019: 1-15. | 
																													
																						| 10 | LIANG J, WANG M, ZHOU C, et al. PATA: fuzzing with path aware taint analysis[C]// Proceedings of the 2022 IEEE Symposium on Security and Privacy. Piscataway: IEEE, 2022: 1-17. | 
																													
																						| 11 | LUK C K, COHN R, MUTH R, et al. Pin: building customized program analysis tools with dynamic instrumentation[J]. ACM SIGPLAN Notices, 2005, 40(6): 190-200. | 
																													
																						| 12 | KEMERLIS V P, PORTOKALIDIS G, JEE K, et al. libdft: practical dynamic data flow tracking for commodity systems [J]. ACM SIGPLAN Notices, 2012, 47(7): 121-132. | 
																													
																						| 13 | RAWAT S, JAIN V, KUMAR A, et al. VUzzer: application-aware evolutionary fuzzing [C]// Proceedings of the 24th Annual Network and Distributed System Security Symposium. Reston, VA: Internet Society, 2017: 1-14. | 
																													
																						| 14 | DENG P, YANG Z, ZHANG L, et al. NestFuzz: enhancing fuzzing with comprehensive understanding of input processing logic[C]// Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security. New York: ACM, 2023: 1272-1286. | 
																													
																						| 15 | CHEN P, CHEN H. Angora: efficient fuzzing by principled search[C]// Proceedings of the 2018 IEEE Symposium on Security and Privacy.Piscataway: IEEE, 2018: 711-725. | 
																													
																						| 16 | SHI J, ZOU W, ZHANG C, et al. CAMFuzz: explainable fuzzing with local interpretation [J]. Cybersecurity, 2022, 5: No.17. | 
																													
																						| 17 | 倪萍,陈伟. 基于模糊测试的反射型跨站脚本漏洞检测[J]. 计算机应用, 2021, 41(9): 2594-2601. | 
																													
																						|  | NI P, CHEN W. Reflective cross-site scripting vulnerability detection based on fuzzing test [J]. Journal of Computer Applications, 2021, 41(9): 2594-2601. | 
																													
																						| 18 | 庄园,曹文芳,孙国凯,等. 基于生成对抗网络与变异策略结合的网络协议漏洞挖掘方法[J]. 计算机科学, 2023, 50(9): 44-51. | 
																													
																						|  | ZHUANG Y, CAO W F, SUN G K, et al. Network protocol vulnerability mining method based on the combination of generative adversarial network and mutation strategy[J]. Computer Science, 2023, 50(9): 44-51. | 
																													
																						| 19 | QIN S, HU F, MA Z, et al. NSFuzz: towards efficient and state-aware network service fuzzing[J]. ACM Transactions on Software Engineering and Methodology, 2023, 32(6): No.160. | 
																													
																						| 20 | ZHAO B, LI Z, QIN S, et al. StateFuzz: system call-based state-aware Linux driver fuzzing [C]// Proceedings of the 31st USENIX Security Symposium. Berkeley: USENIX Association, 2022: 3273-3289. | 
																													
																						| 21 | LEMIEUX C, SEN K. FairFuzz: a targeted mutation strategy for increasing greybox fuzz testing coverage [C]// Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering. New York: ACM, 2018: 475-485. | 
																													
																						| 22 | WANG Y, JIA X, LIU Y, et al. Not all coverage measurements are equal: fuzzing by coverage accounting for input prioritization[C]// Proceedings of the 2020 Annual Network and Distributed System Security Symposium. Reston, VA: Internet Society, 2020: 1-17. | 
																													
																						| 23 | FIORALDI A, MAIER D, EIßFELDT H, et al. AFL++: combining incremental steps of fuzzing research [C]// Proceedings of the 14th USENIX Workshop on Offensive Technologies. Berkeley: USENIX Association, 2020: 3273-3289. | 
																													
																						| 24 | DOLAN-GAVITT B, HULIN P, KIRDA E, et al. LAVA: large-scale automated vulnerability addition [C]// Proceedings of the 2016 IEEE Symposium on Security and Privacy. Piscataway: IEEE, 2016: 110-121. | 
																													
																						| 25 | LATTNER C, ADVE V. LLVM: a compilation framework for lifelong program analysis & transformation [C]// Proceedings of the 2004 International Symposium on Code Generation and Optimization. Piscataway: IEEE, 2004: 75-86. |