Character-level word encoding deep learning model for combating cyber threats in phishing URL detection

Document Type

Article

Source of Publication

Computers and Electrical Engineering

Publication Date

5-1-2022

Abstract

A cyber threat is generally a malicious activity that damages or steals data, or something that disrupts digital life. Such threats include viruses, security breaches, DoS attacks, and data theft. Phishing is a type of cyber threat whereby the attackers mimic a genuine URL or a webpage and steal user data, 21% fall into the phishing category. The novel approach of using the character-level encoding of URLs is introduced. Unlike word-level encoding, the use of character-level encoding decreases the discrete workspace and can be effective even in an energy-constrained environment. The experimental results of comparisons to other state-of-the-art methods demonstrate that the proposed method achieved 98.12% of true positive instances. Moreover, Conclusions: An experimental evaluation was performed to demonstrate the efficiency, and it was observed that the accuracy reached an all-time high of 98.13%. the experiments prove that the proposed method can operate efficiently even in energy-saving modes of phishing detection systems.

ISSN

0045-7906

Publisher

Elsevier BV

Volume

100

Disciplines

Computer Sciences

Keywords

cyber threat, deep learning, deep learning model, machine learning, phishing

Scopus ID

85125833672

Indexed in Scopus

yes

Open Access

no

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