关键词: 网络安全攻击, 威胁情报, 命名实体识别, 深度学习, 挑战分析

Abstract: In the face of increasingly complex network security attacks, it is very important to quickly obtain the latest network threat intelligence for realtime identification, blocking and tracking of network attacks. The key to solve this problem is how to obtain network threat intelligence data effectively, and named entity recognition technology is one of the hot technologies to solving this problem. This paper systematically analyzes several named entity recognition methods based on deep learning, and then designs a named entity recognition model suitable for threat intelligence field, and carries out experimental verification and analysis. Finally, the challenges faced by named entity recognition methods and their development prospects in the field of network security are analyzed and prospected.

Key words: network security attacks, threat intelligence, named entity recognition, deep learning, challenge analysis