Fractal tools in terrorist and financial crime prevention

Abstract

Information society imposes globalization and universality of values. In these circumstances, terrorism, institutional political violence which targets trying to achieve the morbid fear of provoking a spectacular way, inappropriately given conditions, becomes a real threat not only to the nations but also to politics on the global level. In 1996, the International Monetary Fund estimated that 2–5% of the worldwide global economy involved laundered money. Today, intelligence activities in preventing and combating terrorism include financial investigations and money laundering for the purpose of financing terrorism, resulting in broadening of the scope of data to the level which makes it impossible for human logical evaluation. Technologies development that enables increasing capacity of speed and the amount of data processing has enabled defining, analyzing and exploring more and more models. This led to the idea of computer experiments and simulations trying to get to more complex planning and forecasting for the purpose of countering terrorism and “dirty” money transaction, as highly dangerous, complex and variable phenomena. This presentation aims at quotation the wide spectrum of mathematically founded fractal concepts suited to generate computer models of anti-terrorist activities. In this sense, the logistic behind the items connected with detecting and recognizing degree of terroristic threat by comparing fractal structure of people’s faces, fast search through the databases of faces and fingerprints. The speed of searching processes is of vital importance which promotes the crucial importance of compression and data reduction with preservation of regularity. Especially important are analytic forecasting of missing visual data and forms, to supplement the empirical evidences and records. All these operations are possible with higher degree of knowledge utilization and adaptation of virtual reality in the fight against terrorism and different forms of money laundering. The results indicate that the achievements implementation of the concept of fractals depends on substantial prior knowledge, environmental influences, subsystem integration, decentralization and synchronization, and allows us to come up with similar high information technology models, but not necessarily to enable identification of the authentic features of the various anomalies that result in objectively a social consequences. In this sense, we conclude that the application of information technology in the fight against terrorism, based on the concept of fractals has its place in the arsenal of anti-terroristic prevention.