UMBC at SemEval-2018 Task 8: Understanding Text about Malware
Links to Fileshttps://ebiquity.umbc.edu/paper/html/id/821/UMBC-at-SemEval-2018-Task-8-Understanding-Text-about-Malware
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Type of Work7 pages
conference paper pre-print
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natural language processing
UMBC Ebiquity Research Group
We describe the systems developed by the UMBC team for 2018 SemEval Task 8, SecureNLP (Semantic Extraction from CybersecUrity REports using Natural Language Processing). We participated in three of the sub-tasks: (1) classifying sentences as being relevant or irrelevant to malware, (2) predicting token labels for sentences, and (4) predicting attribute labels from the Malware Attribute Enumeration and Characterization vocabulary for defining malware characteristics. We achieved F1 scores of 50.34/18.0 (dev/test), 22.23 (test-data), and 31.98 (test-data) for Task1, Task2 and Task2 respectively. We also make our cybersecurity embeddings publicly available at https://bit.ly/cybr2vec.