Visible to the public Text Analytics for Security: Tutorial

TitleText Analytics for Security: Tutorial
Publication TypeConference Paper
Year of Publication2016
AuthorsXie, Tao, Enck, William
Conference NameProceedings of the Symposium and Bootcamp on the Science of Security
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-4277-3
KeywordsHuman Behavior, human expectations, Metrics, natural language processing, pubcrawl, Resiliency, security, text analytics
Abstract

Computing systems that make security decisions often fail to take into account human expectations. This failure occurs because human expectations are typically drawn from in textual sources (e.g., mobile application description and requirements documents) and are hard to extract and codify. Recently, researchers in security and software engineering have begun using text analytics to create initial models of human expectation. In this tutorial, we provide an introduction to popular techniques and tools of natural language processing (NLP) and text mining, and share our experiences in applying text analytics to security problems. We also highlight the current challenges of applying these techniques and tools for addressing security problems. We conclude the tutorial with discussion of future research directions.

URLhttp://doi.acm.org/10.1145/2898375.2898397
DOI10.1145/2898375.2898397
Citation Keyxie_text_2016