Soon after the 9/11 attacks, some officials recommended that large-scale data mining be used as a method for identifying potential terrorist activity. At its core, data mining involves finding previously unknown patterns or relationships in large databases through the use of automated algorithms. The idea was that federal, state and local agencies could assemble numerous types of data on individuals (such as commercial data consolidators’ personal dossiers, credit card information, and airline passenger data), trawl the resulting data sets, and find patterns of activity that would identify potential terrorists.
The U.S. federal government and state and local agencies have made progress in developing processes for reporting and sharing information critical to terrorist activity through suspicious activity reports (SARs). Yet, there has been little federal guidance provided on how to analyze SARs. We are developing improved law enforcement methods for collecting, processing, and analyzing information on suspicious activities potentially related to terrorism. The project has four phases, with the first two phases serving as preparatory activities for Phases III and IV:
Phase I, Case Studies—Conduct structured case studies of prior terrorist plots to identify the types of suspicious behaviors and means of reporting that most frequently led to discovering terrorist activity.
Phase II, Law Enforcement Interviews—Conduct interviews with law enforcement experts to document how SARs are collected and used, problems with current analysis protocols, and recommendations for improvement.
Phase III, Analytic Approaches—Develop analytic processes for the different forms of SAR data, including recommended procedures for filtering cases, for finding relationships between cases, and for prioritizing cases of interest. This task will begin by reviewing existing templates for suspicious activity reports to characterize common fields.
Phase IV, Dissemination—Develop research and educational materials on collecting, processing, and analyzing SAR data for use by law enforcement.
In this project, RTI International, and its subcontractor RAND Corporation, will partner with experts in law enforcement and homeland security, including the Federal Law Enforcement Training Center (FLETC) and the North Carolina State Fusion Center. Findings can be used to inform law enforcement data collection and training initiatives including guidelines and processes used for the Nationwide SAR Initiative (NSI).
A safe and secure food supply is critical to our national security. The recent string of food recalls and foodborne illnesses have created a sense of urgency in addressing gaps in the food safety system, and made safe food a high priority in the U.S. Congress. Early detection and rapid response are challenges that must be met to minimize the impact of a contamination event –whether unintentional or the result of a terrorist act. Researchers from University of North Carolina’s Center for Logistics and Digital Strategy (CLDS) at Kenan-Flagler Business School and the North Carolina Center for Public Health Preparedness (NCPHP) in the Gillings School of Global Public Health have forged a collaboration to improve food safety at the state level. The NCFOODSAFE project will bridge existing gaps in current NC food safety systems by identifying needs and developing new informatics tools that recognize the human element of an intrinsically complex and dynamic process. The project will focus on understanding the communication structures among government agencies and personnel responsible for regulating and overseeing the state’s food safety system and its interplay with other jurisdictions. To demonstrate the potential of the proposed tools to reduce latency, a prototype FEDA (Foodborne Events Data Integration and Analysis) software tool will be built and tested. This project is a first step toward the eventual integration of new capabilities within current NC surveillance and response systems. NCFOODSAFE will align with current national strategic plans for food safety and its results will serve as model for similar efforts in other states.
State and local law enforcement agencies are important partners in preventing terrorism, with responsibilities that include identifying and investigating local terrorist threats and protecting potential targets from attack. To meet these responsibilities, law enforcement must develop better ways to find and analyze pieces of information that could spotlight potential terrorist activity. This research brief focuses on describing methods for finding and analyzing information indicating potential terrorist activity.