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Packet header intrusion detection with binary logistic regression approach in detecting R2L and U2R attacks
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Kamarudin, Muhammad Hilmi, Maple, Carsten, Watson, Tim and Sofian, Hasliza (2016) Packet header intrusion detection with binary logistic regression approach in detecting R2L and U2R attacks. In: International Conference on Cyber Security, Jakarta, Indonesia, 29-31 Oct 2015. Published in: 2015 Fourth International Conference on Cyber Security, Cyber Warfare, and Digital Forensic (CyberSec) ISBN 9781467384995.
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WRAP-packet-header-intrusion-detection-binary-logistics-approach-Kamarudin-2017.pdf - Accepted Version - Requires a PDF viewer. Download (1415Kb) | Preview |
Official URL: http://doi.org/10.1109/CyberSec.2015.28
Abstract
With the rapid growth of the Internet, there are an increasing number of computer threats and attacks. The prevalence of zero-day attack activities has given rise to the need to prevent these attack activities from spreading and damaging the computer system. As such, intrusion detection system (IDS) should satisfy complex requirements and must be durable, manageable and reliable. In this paper, we developed an anomaly-based detection model using a statistical method combined with a binary logistic regression approach. The model, Layer based Anomaly Detection (LbAD) is designed to detect remote to user (R2L) and user to root (U2R) attacks by statistically examining the degree of normal field values within three layer (data link, network, transport) of OSI Seven Layer. The results of the new method outperform the leading existing methods.
Item Type: | Conference Item (Paper) | ||||||||
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Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) |
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Library of Congress Subject Headings (LCSH): | Intrusion detection systems (Computer security), Logistic regression analysis | ||||||||
Journal or Publication Title: | 2015 Fourth International Conference on Cyber Security, Cyber Warfare, and Digital Forensic (CyberSec) | ||||||||
Publisher: | IEEE Computer Society | ||||||||
ISBN: | 9781467384995 | ||||||||
Official Date: | 17 June 2016 | ||||||||
Dates: |
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Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||
Date of first compliant deposit: | 20 November 2017 | ||||||||
Date of first compliant Open Access: | 20 November 2017 | ||||||||
Conference Paper Type: | Paper | ||||||||
Title of Event: | International Conference on Cyber Security | ||||||||
Type of Event: | Conference | ||||||||
Location of Event: | Jakarta, Indonesia | ||||||||
Date(s) of Event: | 29-31 Oct 2015 | ||||||||
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