Phishing URL Detection with Prototypical Neural Network Disentangled by Triplet Sampling

SJ Bu, SB Cho - Computational Intelligence in Security for Information …, 2023 - Springer
Phishing attacks continue to pose a significant threat to internet security, with phishing URLs
being among the most prevalent attacks. Detecting these URLs is challenging, as attackers …

Check for updates Phishing URL Detection with Prototypical Neural Network Disentangled by Triplet Sampling

SJ Bu, SB Cho - … on Computational Intelligence in Security for …, 2023 - books.google.com
Phishing attacks continue to pose a significant threat to internet security, with phishing URLs
being among the most prevalent attacks. Detecting these URLs is challenging, as attackers …

Phishing URL detection via CNN and attention-based hierarchical RNN

Y Huang, Q Yang, J Qin, W Wen - 2019 18th IEEE International …, 2019 - ieeexplore.ieee.org
Phishing websites have long been a serious threat to cyber security. For decades, many
researchers have been devoted to developing novel techniques to detect phishing websites …

Phishing URL detection via capsule-based neural network

Y Huang, J Qin, W Wen - 2019 IEEE 13th International …, 2019 - ieeexplore.ieee.org
As a cyber attack which leverages social engineering and other sophisticated techniques to
steal sensitive information from users, phishing attack has been a critical threat to cyber …

[PDF][PDF] Robust URL Phishing Detection Based on Deep Learning.

A Al-Alyan, S Al-Ahmadi - KSII Transactions on Internet & Information …, 2020 - itiis.org
Phishing websites can have devastating effects on governmental, financial, and social
services, as well as on individual privacy. Currently, many phishing detection solutions are …

TCURL: Exploring hybrid transformer and convolutional neural network on phishing URL detection

C Wang, Y Chen - Knowledge-Based Systems, 2022 - Elsevier
Phishing is a growing threat that involves cybercriminals creating counterfeit websites to lure
victims and obtain their sensitive information, such as login credentials and credit card …

Visualizing and interpreting rnn models in url-based phishing detection

T Feng, C Yue - Proceedings of the 25th ACM Symposium on Access …, 2020 - dl.acm.org
Existing studies have demonstrated that using traditional machine learning techniques,
phishing detection simply based on the features of URLs can be very effective. In this paper …

Segmentation-based phishing URL detection

ES Aung, H Yamana - IEEE/WIC/ACM International Conference on Web …, 2021 - dl.acm.org
Uniform resource locators (URLs), used for referencing web pages, play a vital role in cyber
fraud because of their complicated structure; phishers, or in other words, attackers, employ …

Texception: a character/word-level deep learning model for phishing URL detection

F Tajaddodianfar, JW Stokes… - ICASSP 2020-2020 …, 2020 - ieeexplore.ieee.org
Phishing is the starting point for many cyberattacks that threaten the confidentiality,
availability and integrity of enterprises' and consumers' data. The URL of a web page that …

Real-Time Phishing Detection Based on URL Multi-Perspective Features: Aiming at the Real Web Environment

S Liu, H Wu, G Cheng, X Hu - ICC 2023-IEEE International …, 2023 - ieeexplore.ieee.org
Phishing deceives users' trust through subtle URL and HTML disguises, stealing sensitive
data or spreading malicious viruses. Phishing detection from URLs has been the focus of …