Katrina E. Triezenberg

Ontology in information security: a useful theoretical foundation and methodological tool

The paper introduces and advocates an ontological semantic approach to information security. Both the approach and its resources, the ontology and lexicons, are borrowed from the field of natural language processing and adjusted to the needs of the new domain. The approach pursues the ultimate dual goals of inclusion of natural language data sources as an integral part of the overall data sources in information security applications, and formal specification of the information security community know-how for the support of routine and time-efficient measures to prevent and counteract computer attacks. As the first order of the day, the approach is seen by the information security community as a powerful means to organize and unify the terminology and nomenclature of the field.

The genesis of a script for Bankruptcy in ontological semantics

This paper describes the creation of a script in the framework of ontological semantics as the formal representation of the complex event BANKRUPTCY. This script for BANKRUPTCY serves as the exemplary basis for a discussion of the general motivations for including scripts in NLP, as well as the discovery process for, and format of, scripts for the purposes of processing coreference and inferencing which are required, for example, in high-end Q&A and IE applications.

Why NLP should move into IAS

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.

Reconciling privacy policies and regulations: ontological semantics perspective

How well the privacy policy follows a regulation is one of the current concerns of the user. Such a task can be accomplished by directly querying the policy statement with the regulation text. Automation of the process requires an expressive meaning-based framework for Natural Language Processing (NLP). This paper discusses the Ontological Semantics approach to the issue of verifying compliance and illustrates the potential of utilizing the framework in the domain of Privacy management for NLP-related tasks. As an example a section from BCBS and corresponding HIPAA regulations are used.

Semantic Representation of English Phrasal Verbs

Multi-word expressions present a number of problems for natural language processing, most notably due to the non-compositional nature of their meaning. The pervasiveness of phrasal verbs in texts makes their acquisition a necessary task, and successful approaches to phrasal verb acquisition display exemplary potential to solve many issues related to multi-word expressions in NLP. We describe an ontological semantic approach to the manual lexical acquisition of phrasal verbs for a natural language database. This paper demonstrates the practical issues and tradeoffs associated with phrasal verb acquisition.

Accessing and manipulating meaning of textual and data information for information assurance and security and intelligence information

This extended abstract focuses on the crucial task of accessing meaning directly in natural language texts (NLT) and databases for the purposes of information assurance and security (IAS) and, especially, information intelligence. It is pretty obvious to all those involved in these areas that much if not most of the information that is pertinent for the various tasks in these fields is represented by NLTs and data from the Web, intercepted documents, research and position papers, print and media reports, etc. The paper deals with a unique approach, ontological semantics (OntoSem), that makes it possible to access the comprehensive meaning of texts and databases directly, emulating and approximating human understanding, and to manipulate it in various real-life applications, rather than trying to circumvent semantics with the juxtaposition of practically unimplementable formalisms, increasingly detailed syntactic parsers or ingenious cluster statistics on NLTs, which is most of the field of natural language processing (NLP) has been playing with in the last two decades.