A dual-phase deep learning framework for advanced phishing detection using the novel OptSHQCNN approach

Background Phishing attacks are now regarded as one of the most prevalent cyberattacks that often compromise the security of different communication and internet networks. Phishing websites are created with the goal of generating cyber threats in order to ascertain the user’s financial information....

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Bibliographic Details
Main Authors:	Srikanth Meda, Vangipuram Sesha Srinivas, Killi Chandra Bhushana Rao, Repudi Ramesh, Narasimha Rao Yamarthi
Format:	Article
Language:	English
Published:	PeerJ Inc. 2025-07-01
Series:	PeerJ Computer Science
Subjects:	Phishing attacks Red kite optimization algorithm (RKOA) Convolutional block attention module (CBAM) Shallow hybrid quantum-classical convolutional neural network (SHQCNN) Optimized bidirectional encoder representations from transformers (OptBERT)
Online Access:	https://peerj.com/articles/cs-3014.pdf
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A dual-phase deep learning framework for advanced phishing detection using the novel OptSHQCNN approach

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