Phishing-Deception Data Model for Online Detection and Human Protection

Barraclough, Phoebe and Sexton, Graham (2017) Phishing-Deception Data Model for Online Detection and Human Protection. In: Global Security, Safety and Sustainability - The Security Challenges of the Connected World. Springer, pp. 144-154. ISBN 978-3-319-51063-7

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Official URL: http://dx.doi.org/10.1007/978-3-319-51064-4_13

Abstract

The construction and interaction procedure of phishing and user in the deception mode is presented. We analyses phishing behavior when tempting human in order to construct a phishing-deception human-based data model (PDHDM) based on frequent associated events. The proposed phishing-deception human-based data model is utilized to generate association rules and to accurately classify between phishing and legitimate websites. This approach can reduce false positive rates in phishing detection systems, including a lack of effective dataset. Classification algorithms is employed for training and validation of the model. The proposed approach performance and the existing work is compared. Our proposed method yielded a remarkable result. The finding demonstrates that phishing-deception human-based data model is a promising scheme to develop effective phishing detection systems.

Item Type: Book Section
Uncontrolled Keywords: Phishing behavior, Phishing-human interaction, Phishing websites, Association classification
Subjects: G400 Computer Science
G500 Information Systems
Department: Faculties > Engineering and Environment > Computer Science and Digital Technologies
Depositing User: Becky Skoyles
Date Deposited: 07 Feb 2017 12:30
Last Modified: 07 Feb 2017 12:30
URI: http://nrl.northumbria.ac.uk/id/eprint/29513

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