Investigative Data Mining for Security and Criminal Detection

In a networked environment such as ours, a new entity has evolved: intelligent agent software. Over the past few years, agents have emerged as a new software paradigm; they are in part distributed systems, autonomous programs, and artificial life. The concept of agents is an outgrowth of years of research in the fields of AI and robotics. They represent concepts of reasoning, knowledge representation, and autonomous learning. Agents are automated programs and provide tools for integration across multiple applications and databases, running across open and closed networks. They are a means of retrieving, filtering, managing, monitoring, analyzing, and disseminating information over the Internet, intranets, and other proprietary networks.
Agents represent a new generation of computing systems and are one of the more recent developments in the field of AI. Agents are specific applications with predefined goals, which can run autonomously; for example, an Internet-based agent can retrieve documents based on user-defined criteria. They can also monitor an environment and issue alerts or go into action based on how they are programmed. In the course of investigative data mining projects, for example, agents can serve the function of software detectives, monitoring, shadowing, recognizing, and retrieving information for analysis and case development or real-time alerts.
Agents can be used by investigators and analysts to work on their behalf; for example FinCEN, the U.S. Treasury agency set up to detect money laundering, must review all cash transactions involving dollar amounts of above $10,000. This amounts to roughly...