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Journal of Intelligent Systems and Internet of Things

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Online: 2690-6791 Print: 2769-786X
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Continuous publication

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Open access · Articles freely available online · APC applies after acceptance

Journal of Intelligent Systems and Internet of Things
Full Length Article

Manta Ray Foraging Optimization Algorithm with Deep Learning Assisted Automated Phishing URL Detection Model

SubashiniKsuba.pooja@gmail.com *
* Corresponding Author.

Abstract

In current scenario, phishing attacks are vital threats to cyberspace security. Phishing is one of the common types of scams that attract individuals to access mischievous URLs (Uniform Resource Locators) as well as their personal data like IDs, passwords, and others. Many intelligent attacks have been launched to cheat users by retrieving a trustworthy website or any online platform in order to get data. Phishing URL classification is one of the crucial cybersecurity tasks intended to classify and moderate malevolent web addresses considered to cheat consumers by revealing sensitive data. Numerous researchers in cyberspace are interested in generating intelligent techniques as well as offering security services on a phishing website that grows more clever and malicious daily. Therefore, this study introduces a manta ray foraging optimization with deep learning-based phishing website detection (MRFODL-PWD) technique. The major intention of the MRFODL-PWD technique is to recognize and classify the presence of legitimate or phishing URLs. In the presented MRFODL-PWD technique, several stages of pre-processing to transfer data into a useful setup, and BERT is applied for feature extraction. Moreover, deep belief network (DBN) model can be used for automated phishing URL detection. Furthermore, the MRFO algorithm selects the hyperparameter values of the DBN model. An extensive comparison study stated that the MRFODL-PWD technique accomplishes enhanced phishing URL detection results over other models.

Keywords

Phishing attacks Cybersecurity Deep learning Parameter tuning Manta ray foraging optimization

References

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[19] https://www.alexa.com/

[20] https://phishtank.org/

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, SubashiniKsuba.pooja@gmail.com. "Manta Ray Foraging Optimization Algorithm with Deep Learning Assisted Automated Phishing URL Detection Model." Journal of Intelligent Systems and Internet of Things, vol. , no. , , pp. . DOI:
, S. (). Manta Ray Foraging Optimization Algorithm with Deep Learning Assisted Automated Phishing URL Detection Model. Journal of Intelligent Systems and Internet of Things, (), . DOI:
, SubashiniKsuba.pooja@gmail.com. "Manta Ray Foraging Optimization Algorithm with Deep Learning Assisted Automated Phishing URL Detection Model." Journal of Intelligent Systems and Internet of Things , no. (): . DOI:
, S. () 'Manta Ray Foraging Optimization Algorithm with Deep Learning Assisted Automated Phishing URL Detection Model', Journal of Intelligent Systems and Internet of Things, (), pp. . DOI:
S. Manta Ray Foraging Optimization Algorithm with Deep Learning Assisted Automated Phishing URL Detection Model. Journal of Intelligent Systems and Internet of Things. ;():. DOI:
S. , "Manta Ray Foraging Optimization Algorithm with Deep Learning Assisted Automated Phishing URL Detection Model," Journal of Intelligent Systems and Internet of Things, vol. , no. , pp. , . DOI:
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