• 发表刊物：Computer Networks
• 影响因子：4.4
• 摘要：Cyberspace mapping is of great significance to the research of network security. The current work of cyberspace mapping is mainly based on IPv4 address. Due to the exhaustion of IPv4 address allocation, the world has begun to vigorously promote the deployment of IPv6 address. However, due to the wide range of IPv6 address space, the traditional exhaustive search detection method cannot be applied to IPv6 address detection. In order to find active IPv6 addresses, researchers have proposed to build a target address generation model to generate high-quality candidate target detection address set, so as to provide support for IPv6 address space exploration work. Nowadays, many researchers have proposed IPv6 target address generation models. However, the existing target address generation model still has the problems of low hit rate and single address generation pattern. In order to generate more active and diverse candidate target detection address set, We propose an IPv6 active address detection model based on the diffusion model. First, the collected seed addresses will be divided according to the interface identifier type, and then the divided address set will complete the transformation from discrete data to continuous data. After that, the transformed data will be input into the diffusion model for IPv6 address generation. Finally, alias checking will be performed on the generated addresses to reduce the waste of detection resources. The experimental results show that the IPv6 address generation model based on diffusion model has a higher hit rate than other existing address generation algorithms.
• 关键字：IPv6 addressDeep learningDiffusion modelAddress detectionNetwork security
• 文献类型：JCR 一区
• 是否译文：否