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Authors: Adriana-Cristina Enache and Valentin Sgârciu

Affiliation: University Politehnica of Bucharest, Romania

Keyword(s): Intrusion Detection, SVM, Bat Algorithm, Binary Bat Algorithm, Lévy Flights.

Related Ontology Subjects/Areas/Topics: Information and Systems Security ; Intrusion Detection & Prevention ; Network Security ; Wireless Network Security

Abstract: As new security intrusions arise so does the demand for viable intrusion detection systems. These solutions must deal with huge data volumes, high speed network traffics and countervail new and various types of security threats. In this paper we combine existing technologies to construct an Anomaly based Intrusion Detection System. Our approach improves the Support Vector Machine classifier by exploiting the advantages of a new swarm intelligence algorithm inspired by the environment of microbats (Bat Algorithm). The main contribution of our paper is the novel feature selection model based on Binary Bat Algorithm with Lévy flights. To test our model we use the NSL-KDD data set and empirically prove that Lévy flights can upgrade the exploration of standard Binary Bat Algorithm. Furthermore, our approach succeeds to enhance the default SVMclassifier and we obtain good performance measures in terms of accuracy (90.06%), attack detection rate (95.05%) and false alarm rate (4.4%) for unkn own attacks. (More)

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Paper citation in several formats:
Enache, A. and Sgârciu, V. (2014). Enhanced Intrusion Detection System Based on Bat Algorithm-support Vector Machine. In Proceedings of the 11th International Conference on Security and Cryptography (ICETE 2014) - SECRYPT; ISBN 978-989-758-045-1; ISSN 2184-3236, SciTePress, pages 184-189. DOI: 10.5220/0005015501840189

@conference{secrypt14,
author={Adriana{-}Cristina Enache. and Valentin Sgârciu.},
title={Enhanced Intrusion Detection System Based on Bat Algorithm-support Vector Machine},
booktitle={Proceedings of the 11th International Conference on Security and Cryptography (ICETE 2014) - SECRYPT},
year={2014},
pages={184-189},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005015501840189},
isbn={978-989-758-045-1},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Security and Cryptography (ICETE 2014) - SECRYPT
TI - Enhanced Intrusion Detection System Based on Bat Algorithm-support Vector Machine
SN - 978-989-758-045-1
IS - 2184-3236
AU - Enache, A.
AU - Sgârciu, V.
PY - 2014
SP - 184
EP - 189
DO - 10.5220/0005015501840189
PB - SciTePress

- Science and Technology Publications, Lda.
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