Generative adversarial network-based AFL seed optimization method and system

The invention relates to an AFL seed optimization method and system based on a generative adversarial network, and belongs to the technical field of information security. According to the AFL seed optimization method and system based on the generative adversarial network provided by the invention, the idea of adversarial game training of the generative adversarial network model is utilized, the effect of optimizing the initial test cases is achieved through continuous loop iteration, on one hand, more initial test cases can be provided, more data support is provided for fuzzy testing, and on the other hand, the optimization of the initial test cases is facilitated; and on the other hand, the initial test case can be continuously optimized, the effectiveness of the seeds is enhanced, more new execution paths are triggered, and a new solution and a new research idea are provided for improving the efficiency and the success rate of AFL vulnerability mining. 本发明涉及一种基于生成对抗网络的AFL种子优化方法及系统，属于信息安全技术领域。本发明提供的基于生成对抗网络的