Neural networks applied in intrusion detection systems

Information is one of the most valuable possessions today. As the Internet expands both in number of hosts connected and number of services provided, security has become a key issue for the technology developers. This work presents a prototype of an intrusion detection system for TCP/IP networks. The system works by capturing packets and using a neural network to identify an intrusive behavior within the analyzed data stream. The identification is based on previous well know intrusion profiles. The system is adaptive, since new profiles can be added to the data base and the neural network retrained to consider them. We present the proposed model, the results achieved and the analysis of an implemented prototype.