A Honeybee-Inspired Framework for a Smart City Free of Internet Scams

Internet scams are fraudulent attempts aim to lure computer users to reveal their credentials or redirect their connections to spoofed webpages rather than the actual ones. Users’ confidential information, such as usernames, passwords, and financial account numbers, is the main target of these fraud...

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Bibliographic Details
Main Authors: Abdulghani Ali Ahmed, Abdulghani Ali Ahmed, Ali Al-Bayatti, Ali Al-Bayatti, Mubarak Saif, Mubarak Saif, Waheb A. Jabbar, Waheb A. Jabbar, Taha H. Rassem, Taha H. Rassem
Format: Article
Language:English
Published: Mdpi 2023
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Online Access:http://eprints.uthm.edu.my/9596/1/J16111_8f5e7f3987a954b227dc88ab579f38f7.pdf
http://eprints.uthm.edu.my/9596/
https://doi.org/10.3390/s23094284
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Institution: Universiti Tun Hussein Onn Malaysia
Language: English
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Summary:Internet scams are fraudulent attempts aim to lure computer users to reveal their credentials or redirect their connections to spoofed webpages rather than the actual ones. Users’ confidential information, such as usernames, passwords, and financial account numbers, is the main target of these fraudulent attempts. Internet scammers often use phishing attacks, which have no boundaries, since they could exceed hijacking conventional cyber ecosystems to hack intelligent systems, which emerged recently for the use within smart cities. This paper therefore develops a real-time framework inspired by the honeybee defense mechanism in nature for filtering phishing website attacks in smart cities. In particular, the proposed framework filters phishing websites through three main phases of investigation: PhishTank-Match (PM), Undesirable-Absent (UA), and Desirable-Present (DP) investigation phases. The PM phase is used at first in order to check whether the requested URL is listed in the blacklist of the PhishTank database. On the other hand, the UA phase is used for investigation and checking for the absence of undesirable symbols in uniform resource locators (URLs) of the requested website. Finally, the DP phase is used as another level of investigation in order to check for the presence of the requested URL in the desirable whitelist. The obtained results show that the proposed framework is deployable and capable of filtering various types of phishing website by maintaining a low rate of false alarms.