Logic-Based Regulatory Conformance Checking

In this paper, we describe an approach to formally assess whether an organization conforms to a body of regulation. Conformance is cast as a model checking question where the regulation is represented in a logic that is evaluated against an abstract model representing the operations of an organization. Regulatory bases are large and complex, and the long term goal of our work is to be able to use natural language processing (NLP) to assist in the translation of regulation to logic. We argue that the translation of regulation to logic should proceed one sentence at a time. A challenge in taking this approach arises from the fact that sentences is regulation often refer to others. We motivate the need for a formal representation of regulation to accommodate references between statements. We briefly describe a logic in which statements can refer to and reason about others. We then discuss preliminary work on using NLP to assist in the translation of regulatory sentences into logic. Comments 14th Monterey Workshop (2007), Monterey, CA, September 10-13, 2007. This conference paper is available at ScholarlyCommons: http://repository.upenn.edu/cis_papers/392 Logic-based Regulatory Conformance Checking Nikhil Dinesh, Aravind Joshi, Insup Lee, and Oleg Sokolsky Department of Computer Science University of Pennsylvania Philadelphia, PA 19104, USA {nikhild,joshi,lee,sokolsky}@seas.upenn.edu Abstract. In this paper, we describe an approach to formally assess whether an organization conforms to a body of regulation. Conformance is cast as a model checking question where the regulation is represented in a logic that is evaluated against an abstract model representing the operations of an organization. Regulatory bases are large and complex, and the long term goal of our work is to be able to use natural language processing (NLP) to assist in the translation of regulation to logic. In this paper, we describe an approach to formally assess whether an organization conforms to a body of regulation. Conformance is cast as a model checking question where the regulation is represented in a logic that is evaluated against an abstract model representing the operations of an organization. Regulatory bases are large and complex, and the long term goal of our work is to be able to use natural language processing (NLP) to assist in the translation of regulation to logic. We argue that the translation of regulation to logic should proceed one sentence at a time. A challenge in taking this approach arises from the fact that sentences is regulation often refer to others. We motivate the need for a formal representation of regulation to accomodate references between statements. We briefy describe a logic in which statements can refer to and reason about others. We then discuss preliminary work on using NLP to assist in the translation of regulatory sentences into logic.