Detection of phishing URLs with deep learning based on GAN-CNN-LSTM network and swarm intelligence algorithms

Cevat Rahebi

Phishing attacks are one of the challenges of the Internet and its users. Phishing attacks are an example of social engineering attacks based on deceiving users. In phishing attacks, fake pages that are very similar to legitimate pages are created on the Internet. In phishing attacks, the victim is directed to fake pages, and their valuable information is stolen. Most of the targets of phishing attacks include online payment services, banking, and online sales, so the losses of these attacks are significant. One way to detect phishing attacks is to use machine learning and deep learning method ...Daha fazlası

Makale 2024 Signal Image Video Process 14 Görüntülenme

Erişime Açık

A cyber defense system against phishing attacks with deep learning game theory and LSTM-CNN with African vulture optimization algorithm (AVOA)

Cevat Rahebi

Phishing attacks pose a significant threat to online security, utilizing fake websites to steal sensitive user information. Deep learning techniques, particularly convolutional neural networks (CNNs), have emerged as promising tools for detecting phishing attacks. However, traditional CNN-based image classification methods face limitations in effectively identifying fake pages. To address this challenge, we propose an image-based coding approach for detecting phishing attacks using a CNN-LSTM hybrid model. This approach combines SMOTE, an enhanced GAN based on the Autoencoder network, and swar ...Daha fazlası

Makale 2024 International Journal of Information Security 20 Görüntülenme