Intrusion Detection System in Ad Hoc Networks with Artificial Neural Networks and Algorithm K-Means

There has been a great technological advance in the infrastructure of mobile technologies. The increase in the use of wireless local area networks and the use of services from satellites is also noticeable. The high rate of use of mobile devices for various purposes brings the need to monitor the wireless networks to ensure the integrity and confidentiality of the information. Therefore it is necessary to quickly and efficiently identify the normal and abnormal traffic of these wireless networks so that their administrators can take action. This paper presents a proposal for an Ad Hoc Wireless Intrusion Detection System composed of two stages, based on data grouping through the K-Means and Artificial Neural Networks algorithm through the Multilayer Perceptron algorithm, for the detection and classification of anomalies caused by attacks on the networks of Computers.