Network Anomaly Detection Using PSO-ANN

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Provided by: International Journal of Computer Applications
Topic: Security
Format: PDF
In this paper, the continue from the last research paper done, thus it is proposed a data mining based anomaly detection system, aiming to detect volume anomalies, using Simple Network Management Protocol (SNMP) monitoring. The method is novel in terms of combining the use of Digital Signature of Network Segment (DSNS) with the evolutionary technique called Particle Swarm Optimization (PSO) and neural network training, applied in a real data set. The DSNS is a baseline that consists of different normal behavior profiles to a specific network device or segment, generated by the GBA tool (automatic backbone management), using data collected from SNMP objects.
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