An intrusion detection system based on a hybrid Tabu-genetic algorithm

Autor: Gülesin Sena Daş, Khaled Bakour, H. Murat Unver
Přispěvatelé: Kırıkkale Üniversitesi
Rok vydání: 2017
Předmět:
Zdroj: 2017 International Conference on Computer Science and Engineering (UBMK).
DOI: 10.1109/ubmk.2017.8093378
Popis: 2017 International Conference on Computer Science and Engineering (UBMK) -- OCT 05-08, 2017 -- Antalya, TURKEY WOS: 000426856900041 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. IEEE Adv Technol Human, Istanbul Teknik Univ, Gazi Univ, Atilim Univ, TBV, Akdeniz Univ, Tmmob Bilgisayar Muhendisleri Odasi
Databáze: OpenAIRE