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An intrusion detection system is an important component of the computer and information security framework. Its main goal is to differentiate between normal activities of the system and behaviors that can be classified as suspicious or intrusive. The research aims at the design, implementation and evaluation of an intelligent intrusion detection system based on artificial neural network that can promptly detect attacks, no matter they are known or not. In this system, neural network is used to learn about the normal users' behavior to form the network traffic that only contains information about normal users. When the learning is over, the system is tested with the network traffic that contains both attacks and normal data. A simulated computer network is used to test the system performance. In experiments, system performance has been compared with other research works and the results in experiments are very promising.