SecureNLP-Classification-of-Relevant-Sentences-to-Malware

With the increasing number of cyber-security threats and vulnerabilities, it has become important to identify these quickly to take the appropriate action. There is a large amount of malware related information on the web and it becomes difficult for security researchers to go through this information to find the useful content within it. There is a need to be able to extract the highly relevant sentences without having to read through the entire malware reports or text. In our project, we aim to work on classifying sentences as being relevant to malware or not. This is a part of the Semeval 2018 Task 8. We have used deep learning along with other methods for this task. We have tried different approaches and compare the results of our experiments.