6VecLM: Language Modeling in Vector Space for IPv6 Target Generation

Fast IPv6 scanning is challenging in the field of network measurement as it requires exploring whole address space but limited by current computational power. Researchers propose to obtain possible active target candidate sets probe algorithmically analyzing seed sets. However, addresses lack semantic information and contain numerous addressing schemes, leading difficulty designing effective algorithms. In this paper, we introduce our approach 6VecLM explore achieving such generation The architecture can map into a vector interpret relationships uses Transformer build language models for predicting sequence. Experiments indicate that perform classification on space. By adding new approach, model possesses controllable word innovation capability compared conventional models. work outperformed state-of-the-art algorithms two datasets reaching more quality