Why NLP should move into IAS

  • Authors:
  • Victor Raskin;Sergei Nirenburg;Mikhail J. Atallah;Christian F. Hempelmann;Katrina E. Triezenberg

  • Affiliations:
  • Purdue University, W. Lafayette, IN;New Mexico State University, Las Cruces, NM;Purdue University, W. Lafayette, IN;Purdue University, W. Lafayette, IN;Purdue University, W. Lafayette, IN

  • Venue:
  • COLING-Roadmap '02 Proceedings of the 2002 COLING workshop: A roadmap for computational linguistics - Volume 13
  • Year:
  • 2002

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Abstract

The paper introduces the ways in which methods and resources of natural language processing (NLP) can be fruitfully employed in the domain of information assurance and security (IAS). IAS may soon claim a very prominent status both conceptually and in terms of future funding for NLP, alongside or even instead of established applications, such as machine translation (MT). After a brief summary of theoretical premises of NLP in general and of ontological semantics as a specific approach to NLP developed and/or practiced by the authors, the paper reports on the interaction between NLP and IAS through brief discussions of some implemented and planned NLP-enhanced IAS systems at the Center for Education and Research in Information Assurance and Security (CERIAS). The rest of the paper deals with the milestones and challenges in the future interaction between NLP and IAS as well as the role of a representational, meaning-based NLP approach in that future.