| Autor: |
Ahmed AA; School of Computer Science and Informatics, De Montfort University, The Gateway, Leicester LE1 9BH, UK., Al-Bayatti A; School of Computer Science and Informatics, De Montfort University, The Gateway, Leicester LE1 9BH, UK., Saif M; Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Parit Raja 86400, Malaysia., Jabbar WA; School of Engineering and the Built Environment, Birmingham City University, Birmingham B4 7XG, UK., Rassem TH; School of Computer Science and Informatics, De Montfort University, The Gateway, Leicester LE1 9BH, UK. |
| Jazyk: |
angličtina |
| Zdroj: |
Sensors (Basel, Switzerland) [Sensors (Basel)] 2023 Apr 26; Vol. 23 (9). Date of Electronic Publication: 2023 Apr 26. |
| DOI: |
10.3390/s23094284 |
| Abstrakt: |
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. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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