[Objective] This paper provides directions for a new scholarly system, aiming to identify and summarize intelligence analysis methods for security intelligence. [Methods] Firstly, we retrieved full-text security intelligence literature, and tagged them using Character-level method. Then, we constructed the corpus for the extraction of intelligence analysis methods. Finally, we compared the performance of two deep learning models with the experimental data. [Results] For the BiLSTM model, the precision, recall and F1 values were 81.71%, 77.26%, and 79.36% respectively. For the BiLSTM-CRF model, the precision, recall and F1 values were 84.71%, 79.25%, and 81.83%. [Limitations] The pronouns that represent intelligence analysis methods are not taken into consideration. [Conclusions] We could use deep learning model to extract intelligence analysis methods for security intelligence.