UPM Institutional Repository

Intrusion detection system in secure shell traffic in cloud environment


Barati, Mehdi and Abdullah, Azizol and Udzir, Nur Izura and Behzadi, Mostafa and Mahmod, Ramlan and Mustapha, Norwati (2014) Intrusion detection system in secure shell traffic in cloud environment. Journal of Computer Science, 10 (10). pp. 2029-2036. ISSN 1549-3636; ESSN: 1552-6607


Due to growth of Cloud computing usage, the need to apply encrypted protocols to provide confidentiality and integrity of data increases dramatically. Attacker can take advantage of these protocols to hide the intrusion and evade detection. Many traditional attack detection techniques have been proposed to provide security in the networks but none of them can be implemented properly in encrypted networks. This study investigates a popular attack in Secure Shell (SSH), known as brute force attack and provides an efficient method to detect this attack. Brute force attack is launched by implementing a client-server SSH model in a private Cloud environment and the traffics regarding attack and normal are captured on the server. Then, representative features of traffic are extracted and used by the Multi-Layer Perceptron model of Artificial Neural Network to classify the attack and normal traffic. Results gained by this method show that the proposed model is successfully capable to detect this attack with high accuracy and low false alarm.

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Additional Metadata

Item Type: Article
Divisions: Faculty of Computer Science and Information Technology
DOI Number: https://doi.org/10.3844/jcssp.2014.2029.2036
Publisher: Science Publications
Keywords: Brute force attack; Intrusion detection system; Cloud environment; Encrypted traffic; SSH traffic; Machine learning; ANN
Depositing User: Nurul Ainie Mokhtar
Date Deposited: 10 Dec 2015 00:55
Last Modified: 28 Sep 2018 01:53
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3844/jcssp.2014.2029.2036
URI: http://psasir.upm.edu.my/id/eprint/34251
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