Padia, AnkurRoy, ArpitaSatyapanich, Taneeya W.Ferraro, FrancisPan, ShimeiPark, YoungjaJoshi, AnupamFinin, Tim2018-10-232018-10-232018-06-05http://hdl.handle.net/11603/1164110.18653/v1/S18-1142Proceedings of International Workshop on Semantic Evaluation (SemEval-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.7 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.Attribution 4.0 Internationalcybersecurityinformation extractionnatural language processingUMBC Ebiquity Research GroupText