Improving effectiveness of honeypots: predicting targeted destination port numbers during attacks using J48 algorithm

Gangabissoon, Tanveer, Nathoo, Amaan, Ramhith, Rakshay, Gopee, Bhooneshwar and Bekaroo, Girish ORCID: https://orcid.org/0000-0003-1753-4300 (2019) Improving effectiveness of honeypots: predicting targeted destination port numbers during attacks using J48 algorithm. Smart and Sustainable Engineering for Next Generation Applications: Proceeding of the Second International Conference on Emerging Trends in Electrical, Electronic and Communications Engineering (ELECOM 2018), November 28–30, 2018, Mauritius. In: ELECOM 2018: 2nd International Conference on Emerging Trends in Electrical, Electronic and Communications Engineering, 28-30 Nov 2018, Mauritius. ISBN 9783030182397, e-ISBN 9783030182403. ISSN 1876-1100 (doi:10.1007/978-3-030-18240-3_21)

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Abstract

During recent years, there has been an increase in cyber-crime and cybercriminal activities around the world and as countermeasures, effective attack prevention and detection mechanisms are needed. A popular tool to augment existing attack detection mechanisms is the Honeypot. It serves as a decoy for luring attackers, with the purpose to accumulate essential details about the intruder and techniques used to compromise systems. In this endeavor, such tools need to effectively listen and keep track of ports on hosts such as servers and computers within networks. This paper investigates, analyzes and predicts destination port numbers targeted by attackers in order to improve the effectiveness of honeypots. To achieve the purpose of this paper, the J48 decision tree classifier was applied on a database containing information on cyber-attacks. Results revealed insightful information on key destination port numbers targeted by attackers, in addition to how these targeted ports vary within different regions around the world.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 561)
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 29764
Notes on copyright: This is a post-peer-review, pre-copyedit version of an paper published in Smart and Sustainable Engineering for Next Generation Applications. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-18240-3_21
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Depositing User: Girish Bekaroo
Date Deposited: 14 May 2020 08:23
Last Modified: 21 May 2020 23:09
URI: https://eprints.mdx.ac.uk/id/eprint/29764

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