Accountable Information Usage in Fusion Center Information Sharing Environments


Fusion Centers are critical venues for sharing information between and among Federal, State and Local law enforcement and intelligence agencies. To enable seamless information flow while assuring that privacy and security policies are complied with, Fusion Centers require tools to enable machine-assistant analysis of relevant policies and mechanisms built into the information infrastructure that provide for accountable information flow.

The tools should be able to accurately represent each rule that applies to each data sharing event. In some cases, sharing will be automatically approved without any human intervention required. In other cases, the main function of the tool will be to offer a human decisionmaker reasoning support in order to decide whether information can be shared and how it can be subsequently used. In all cases, our policy aware systems support Information Accountability that assures the ability to assess compliance with rules in an after-the-fact audit. Information accountability will assure analysts and data users that their well-informed decision to use data will not be second-guessed after the fact and will provide the public and policy makers confidence that uses of sensitive information are done in an accountable manner.

We have conducted basic research into the expression of policies and the automated compliance checking of these policies in various domains using Semantic Web standards and technologies. We will leverage our research to design and implement a set of proof-of-concept accountable information sharing tools that address needed identified in Fusion Center information sharing scenarios.


We are interested in working with students both at UROP and MEng levels. Students interested in this research should email
Lalana Kagal or Danny Weitzner



$Revision: 32314 $
$Date: 2013-09-27 16:51:56 -0400 (Fri, 27 Sep 2013) $