Abstract
At the end of the Cold War, the Intelligence situation (characterized in the past by a confrontation among equals and information scarcity) changed radically to the current situation of today, characterized as an asymmetric threat: on one side, there is still a nation; but on the other, there is a relatively small group of individuals, brought together by a common ideology, usually with ethnic and religious elements. These individuals can only confront their opponent by using subterfuge, deception and terrorist acts. They try to disguise their activities by infiltrating society at large and seeking refuge in anonymity. This kind of conflict has long been analyzed in the military literature under names like low-intensity conflict (LIC) or operation other than war (OOTW) (for more on this perspective, the reader is referred to the classic work by Kitson (Kitson, 1971)). The task of the nations under terrorist threat is to detect the group’s individuals and their intentions before they can carry out destructive actions. For this, their Intelligence services count on large amounts of raw data, obtained from many different sources: signal Intelligence, open sources, tips from informants, friendly governments. However, this data is not always reliable, almost never complete, and the truly interesting events are usually to be found hidden among large amounts of similar-looking facts.
Key Terms in this Chapter
Community: Group of people that share common characteristics; for a community of interest , a common role on a common task; for a community of expertise , a common area of knowledge and professional experience.
Business Intelligence: The process of gathering information in the field of business. The goal is to gain competitive advantage. Information gathered usually refers to customers (their needs, their decision making processes), the market (competitors, conditions in the industry), and general factors that may affect the market (the economy at large, technology, culture).
Intelligence Data Sources: The origin of data captured in the Data Collection phase; it covers both people (HUMINT) or mechanical/technical means (SIGINT, IMINT, MASINT).