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    An intrusion detection system based on a hybrid tabu-genetic algorithm
    (Institute of Electrical and Electronics Engineers Inc., 2017) Bakour, Khaled; Daş, Gülesin Sena; Ünver, H. Murat
    In this paper, we proposed a framework for detecting network's intrusions using Genetic Algorithm (GA) with multiple criteria. First of all, we build an intrusion detection system (IDS) using a pure GA with multiple selection methods. Then, we proposed one of the few hybrid algorithms in the literature, which is hybridized using a GA and a Tabu search (TS) algorithm. The proposed hybrid algorithm and the pure GA were tested to detect malicious traffic using DARPA dataset. The test results revealed that the proposed hybrid algorithm gives a higher Detection Rate (DR) and Detection Accuracy (AC) compared to the pure GA. © 2017 IEEE.