Identificação remota de pontos de acesso utilizando aprendizado de máquina

Abstract

With the evolution of technology, the Internet has become the largest communication channel, mainly through access points (routers) dispersed in various places. With this, there has been a growth in the amount of virtual incidents, such as denial of service attacks, creation of false access points, theft of sensitive information and so on. In this context, even with the advancement of technologies, there are still problems with information security, since systems of prevention, inhibition of virtual incidents and unauthorized access, can not be be totally effective, much less identify the person responsible for the virtual incident. This work has as general objective to develop a tool capable of identifying an access point, through its fingerprints. First, the tool captures information from it for creating your fingerprint. The information captured from an access point will be IEEE 802.11 frames. Then the impressions are stored in a database, and later the ART-1 (Adaptive Resonance Theory) algorithm is applied to create groupings and classify fingerprints.