Machine Learning in Infrastructure Security.
V. Rao Vemuri · 2003
Extended Abstract: Democratic societies throughout the world, it appears, are facing a new type of threat dubbed "asymmetric threat. " In this new threat environment the world governments are faced with a number of low-intensity conflicts characterized by less discriminate attacks on civilian populations, infrastructures and the like. For the purposes of this paper, an asymmetric war is defined as an environment in which a government is faced with a faceless and stateless enemy. Even states can hide behind the façade of a stateless terrorist group and conduct attacks. Contemporary cross-border terrorism is an example. The advent of Internet is a mixed blessing in this context. On one hand the Internet gives the terrorist organizations an opportunity to open a new front in the shape of cyber warfare. On the other hand the internet-based technologies can be used to fight back terrorism. In defense establishments, an often-suggested solution to this terrorism problem is to spin strands of Information Technology (IT) that would weave data gathered from diverse sensors into a vast electronic dragnet. Some defense technologists point out that the types of computerized data sifting and pattern