VHDL Modeling of Intrusion Detection & Prevention System (IDPS) A Neural Network Approach
This addresses network security for organizations by detecting and preventing intrusions, but it is incremental as it applies existing ANN methods to IDPS with hardware implementation.
The paper tackled network security by implementing an artificial neural network (ANN) approach for an intrusion detection and prevention system (IDPS) and converting it to VHDL code, with promising results showing potential applicability for practical IDSs.
The rapid development and expansion of World Wide Web and network systems have changed the computing world in the last decade and also equipped the intruders and hackers with new facilities for their destructive purposes. The cost of temporary or permanent damages caused by unauthorized access of the intruders to computer systems has urged different organizations to increasingly implement various systems to monitor data flow in their network. The systems are generally known as Intrusion Detection System (IDS).Our objective is to implement an artificial network approach to the design of intrusion detection and prevention system and finally convert the designed model to a VHDL (Very High Speed Integrated Circuit Hardware Descriptive Language) code. This feature enables the system to suggest proper actions against possible attacks. The promising results of the present study show the potential applicability of ANNs for developing practical IDSs.