Modified Intrusion Detection System using Fuzzy Genetic Algorithm
نویسنده
چکیده
computing environment is continually growing and changing with new technology and the Internet. In addition, vulnerabilities in this environment are also steadily increasing. So Intrusion Detection Systems (IDS) have turn out to be an important part in provisions of computer and network security. This paper presents a fuzzy-genetic approach to detecting network intrusion. To implement and measure the performance of the system the KDD99 benchmark dataset is used. The KDD99 dataset is a benchmark dataset that is used in various. Genetic algorithm includes a development and collection that uses a chromosome-like data structure and develop the chromosomes using selection, crossover and mutation operators. Fuzzy rule is a machine learning algorithm that can sort network attack data. The results of the proposed system are measured in terms of accuracy, execution time and memory allocation. Results are compared with the existing system which uses sequential algorithm, genetic algorithm or fuzzy algorithm for intrusion detection. Keywords— Fuzzy algorithm, genetic algorithm, fuzzy genetic algorithm, intrusion detection system, KDD Cup 1999 dataset
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