Description

Intrusion Detection System (IDS) monitors network or system activities for malicious activities or policy violations and produces electronic reports to a management station. A cyber-attack is any type of offensive maneuver employed by individuals or whole organizations that targets computer information systems by various means of malicious acts usually originating from an anonymous source that destroys a specified target by hacking into a susceptible system. Perform intrusion detection scheme in SCADA system using feature selection method and classification. Here Fisher Criterion based Genetic Algorithm and Particle Swarm Optimization proposed for feature selection method where important features are selected. Then the selected features are classified with different classes based on the label. Here support vector data description (SVDD) and the kernel principle component analysis. A feature selection method is presented based on Fisher criterion and Genetic optimization, which is called FIG for short. The Fisher criterion is applied to evaluate feature selection results, based on which a genetic optimization algorithm is developed to find out the optimal feature subset from candidate features. Particle Swarm Optimization is a group of variables have their values adjusted closer to the member whose value is closest to the target at any given moment. Imagine a flock of birds circling over an area where they can smell a hidden source of food. >