Natural-language processing support for developing policy-governed software systems

Michael, J.B.; Ong, Vanessa L.; Rowe, Neil C.

doi:10.1109/tools.2001.941679

Cited by 21 publications

(15 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The prototype tool achieved a 96% accuracy in parsing 99 Naval Postgraduate School security policy statements. [18] This supports our hypothesis that domain-specific natural-language processing tools can potentially attain higher accuracy.…”

Section: A Selective History Of the Relationship Between Re And Nlpsupporting

confidence: 79%

Innovations in Natural Language Document Processing for Requirements Engineering

Bērziņš

Martell

Luqi

et al. 2008

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. This paper evaluates the potential contributions of natural language processing to requirements engineering. We present a selective history of the relationship between requirements engineering (RE) and natural-language processing (NLP), and briefly summarize relevant recent trends in NLP. The paper outlines basic issues in RE and how they relate to interactions between a NLP front end and system-development processes. We suggest some improvements to NLP that may be possible in the context of RE and conclude with an assessment of what should be done to improve likelihood of practical impact in this direction.

show abstract

Section: A Selective History Of the Relationship Between Re And Nlpsupporting

confidence: 79%

Innovations in Natural Language Document Processing for Requirements Engineering

Bērziņš

Martell

Luqi

et al. 2008

Lecture Notes in Computer Science

View full text Add to dashboard Cite

show abstract

“…Much similar work , Kagal 2002, Damianou et al 2001) has been done on defining policies to govern the behaviour of many autonomous processes; however, those policies were written in various languages, including natural language (Michael et al 2001). Use of multiple policy languages without having a common vocabulary leads to ambiguity and unnecessary complexity, and also impacts upon the correctness and accuracy of system behaviour if policies are ill-or incompletely specified.…”

Section: Ontology-based Update Policymentioning

confidence: 99%

Selective data replication for distributed geographical data sets

Pascoe

2008

Proceedings of the 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

View full text Add to dashboard Cite

The main purpose of this research is to incorporate additional higher-level semantics into the existing data replication strategies in such a way that their flexibility and performance can be improved in favour of both data providers and consumers. The resulting approach from this research is referred to as the selective data replication system. With this system, the data that has been updated by a data provider is captured and batched into messages known as update notifications. Once update notifications are received by data consumers, they are used to evaluate so-called update policies, which are specified by data consumers containing details on when data replications need to occur and what data needs to be updated during the replications.

show abstract

“…Analyzing natural language to understand policy rules is a difficult task [16]. In order for SPARCLE to be a useful and usable tool, we needed to create a set of grammars that would identify policy elements in each rule with high reliability.…”

Section: Grammar Designmentioning

confidence: 99%

An empirical study of natural language parsing of privacy policy rules using the SPARCLE policy workbench

Brodie

Karat

2006

Proceedings of the Second Symposium on Usable Privacy and Security - SOUPS '06

110

View full text Add to dashboard Cite

Today organizations do not have good ways of linking their written privacy policies with the implementation of those policies. To assist organizations in addressing this issue, our humancentered research has focused on understanding organizational privacy management needs, and, based on those needs, creating a usable and effective policy workbench called SPARCLE. SPARCLE will enable organizational users to enter policies in natural language, parse the policies to identify policy elements and then generate a machine readable (XML) version of the policy. In the future, SPARCLE will then enable mapping of policies to the organization's configuration and provide audit and compliance tools to ensure that the policy implementation operates as intended.In this paper, we present the strategies employed in the design and implementation of the natural language parsing capabilities that are part of the functional version of the SPARCLE authoring utility. We have created a set of grammars which execute on a shallow parser that are designed to identify the rule elements in privacy policy rules. We present empirical usability evaluation data from target organizational users of the SPARCLE system and highlight the parsing accuracy of the system with the organizations' privacy policies. The successful implementation of the parsing capabilities is an important step towards our goal of providing a usable and effective method for organizations to link the natural language version of privacy policies to their implementation, and subsequent verification through compliance auditing of the enforcement logs.

show abstract

Natural-language processing support for developing policy-governed software systems

Abstract: Abstract

Cited by 21 publications

References 8 publications

Innovations in Natural Language Document Processing for Requirements Engineering

Innovations in Natural Language Document Processing for Requirements Engineering

Selective data replication for distributed geographical data sets

An empirical study of natural language parsing of privacy policy rules using the SPARCLE policy workbench

Contact Info

Product

Resources

About