The Study And Implementation Of IDS Based On Artificial Neural Network

As an active security-defence technique,intrusion-detectionoffers realtime protect against interior or exterior attack,andmistaken operation ,as it can hold up an respond intrusion beforethe network is endangered. However,with the diversity of intrusiontechnology,tradition IDS can not fit current networkenvironment ,therefor intelligent technologies must be used.This paper open with some elemental conceptions and theoriesof IDS. The paper analyzes intrusion-detection technique inexisting IDS models and IDS products, discovers they are limitedand hard to meet IDS 's needs which occupies real-time character,adaptability, accuracy and the ability of self-learning.Then study upon on neural network, the paper finds it is verysuitable for the IDS in concept. An intrusion-detection systembased on neural network will play a much role in the theory andpractical if it can be designed and implemented. And the papergives a detailed describing to the deducing of BP algorithm and itsbetterment arithmetic.This paper introduces the neural network technology in IDSmodel, and put forward a detailed design scheme ofintrusion-detection model based on neural network. Great emphasiswas put in key modules. Lastly according experimental throughtraining and intrusion procedure, we get a fairly analysis, whichindicates the neural network has a very great advantage in intrusiondetection. Finally, according to the result, the writer put forwardsome questions and some new ideas.