Extracting Threat Intelligence Relations Using Distant Supervision and Neural Networks

Yali Luo, Shengqin Ao, Ning Luo, Changxin Su, Peian Yang, Zhengwei Jiang

Abstract: Threat intelligence is vital to implementing cyber security. The automated extraction of relations from open-source threat intelligence can greatly reduce the workload of security analysts. However, implementing this feature is hindered by the shortage of labeled training datasets, low accuracy and recall rates of automated models, and limited types of relations that can be extracted.