A System Approach for Evaluating Current and Emerging Army Open-Source Intelligence Tools

摘要

The United States Army maximizes combat effectiveness by synthesizing intelligence on the enemy. Open Source Intelligence, also known as OSINT, is a growing and maturing intelligence discipline that has promising potential for the United States Army. Today's OSINT tools provide various capabilities to enhance privacy and protect organizations from online threats. Although OSINT provides useful information, there are limitations that hinder the effectiveness of intelligence gathering. Our client, the Army Open Source Office (AOO), sponsored our team to develop a methodology to assess the current and emerging OSINT tools and technologies. Our team applies a systems decision process to develop a value model to improve OSINT operations. This paper outlines the systems approach, uses a client-oriented problem statement, and creates a value model. The results indicate that some OSINT tools do not completely meet the Army's requirements. This indicates a significant value gap between the current and desired OSINT tools. The model also makes a cost versus value comparison; however, the costs and tools are classified. This model serves two purposes. First, this model measures the performance of the Army's current toolkit to compare against other available tools. Secondly, this model evaluates emerging tools. Lastly, this model provides the decision maker with quantitative measures of performance to make better decisions on the allocation of resources.