Proceedings of International Workshop on Semantic Evaluation (SemEval-2018)

UMBC at SemEval-2018 Task 8: Understanding Text about Malware

Ankur Padia, Arpita Roy, Taneeya W. Satyapanich, Francis Ferraro, Shimei Pan, Youngja Park, Anupam Joshi, and Tim Finin

June 5, 2018

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.

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Tags: cybersecurity, information extraction, natural language processing

Type: InProceedings

Address: New Orleans, LA, USA

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