Abstract
Computing systems that make security decisions often fail to take into account human expectations. This failure oc- curs 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 introduc- tion to popular techniques and tools of natural language pro- cessing (NLP) and text mining, and share our experiences in applying text analytics to security problems. We also high- light the current challenges of applying these techniques and tools for addressing security problems. We conclude the tu-torial with discussion of future research directions.
Original language | English (US) |
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Pages | 124-125 |
Number of pages | 2 |
DOIs | |
State | Published - 2016 |
Event | Symposium and Bootcamp on the Science of Security, HotSos 2016 - Pittsburgh, United States Duration: Apr 19 2016 → Apr 21 2016 |
Conference
Conference | Symposium and Bootcamp on the Science of Security, HotSos 2016 |
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Country/Territory | United States |
City | Pittsburgh |
Period | 4/19/16 → 4/21/16 |
Keywords
- Security
- human expectations
- text analytics
ASJC Scopus subject areas
- Software
- Human-Computer Interaction
- Computer Vision and Pattern Recognition
- Computer Networks and Communications