A Network Intrusions Detection System based on a Quantum Bio Inspired Algorithm

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2014 by IJETT Journal
Volume-10 Number-8
Year of Publication : 2014
Authors : Omar S. Soliman , Aliaa Rassem


Omar S. Soliman , Aliaa Rassem. "A Network Intrusions Detection System based on a Quantum Bio Inspired Algorithm", International Journal of Engineering Trends and Technology (IJETT), V10(8),370-379 April 2014. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group


Network intrusion detection systems (NIDSs) have a role of identifying malicious activities by monitoring the behavior of networks. Due to the currently high volume of networks trafic in addition to the increased number of attacks and their dynamic properties, NIDSs have the challenge of improving their classification performance. Bio-Inspired Optimization Algorithms (BIOs) are used to automatically extract the the discrimination rules of normal or abnormal behavior to improve the classification accuracy and the detection ability of NIDS. A quantum vaccined immune clonal algorithm with the estimation of distribution algorithm (QVICA-with EDA) is proposed in this paper to build a new NIDS. The proposed algorithm is used as classification algorithm of the new NIDS where it is trained and tested using the KDD data set. Also, the new NIDS is compared with another detection system based on particle swarm optimization (PSO). Results shows the ability of the proposed algorithm of achieving high intrusions classification accuracy where the highest obtained accuracy is 94.8 %.


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Estimation of Distribution Algorithm (EDA), Network Intrusions Detection System (NIDS), Quantum Vaccined Immune Clonal Algorithm (QVICA).