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In several previous investigations, the capability of fuzzy systems to solve different kinds of problems has been demonstrated. Evolutionary fuzzy system hybridizes the approximate reasoning method of fuzzy systems with the learning capability of evolutionary algorithms. The objective of this paper is to demonstrate the ability of evolutionary fuzzy system to deal with intrusion detection classification problem as a new real-world application area. The Evolutionary Fuzzy System would be capable of extracting accurate fuzzy classification rules from network traffic data and applies them to detect normal and intrusive behaviors in computer network. Experiments were performed with KDDCup99 intrusion detection benchmark dataset which has information on computer networks, during normal and intrusive behaviors. The results illustrate that the proposed algorithm achieves more accurate intrusion detection system than several well-known and new methods.