An Anomaly Detection Model in a LAN Using K-NN and High Performance Computing Techniques

Detecting unusual values from large volumes of information produced by network traffic has acquired considerable interest in the network security area. Having a system of detecting anomalous events in a time near their occurrence, it is important for all computer systems in a network. Detecting anomalous values can lead network administrators to identify system failures, take preventative actions and avoid a massive spread. Anomaly detection is a starting point to prevent attacks. In this article, we present a form of data pre-processing to identify anomalies using a supervised classification algorithm, image processing, parallel computing techniques and Graphical Processing Units.