[HTML][HTML] A deep learning-based phishing detection system using CNN, LSTM, and LSTM-CNN

Z Alshingiti, R Alaqel, J Al-Muhtadi, QEU Haq… - Electronics, 2023 - mdpi.com
In terms of the Internet and communication, security is the fundamental challenging aspect.
There are numerous ways to harm the security of internet users; the most common is …

[HTML][HTML] A Deep learning-based innovative technique for phishing detection in modern security with uniform resource locators

EA Aldakheel, M Zakariah, GA Gashgari, FA Almarshad… - Sensors, 2023 - mdpi.com
Organizations and individuals worldwide are becoming increasingly vulnerable to
cyberattacks as phishing continues to grow and the number of phishing websites grows. As …

PDGAN: Phishing detection with generative adversarial networks

S Al-Ahmadi, A Alotaibi, O Alsaleh - Ieee Access, 2022 - ieeexplore.ieee.org
Phishing is a harmful online attack that could lead to identity theft and financial damages.
The demand for high-accuracy phishing detection tools has risen due to the increase of …

[HTML][HTML] Unbalanced web phishing classification through deep reinforcement learning

A Maci, A Santorsola, A Coscia, A Iannacone - Computers, 2023 - mdpi.com
Web phishing is a form of cybercrime aimed at tricking people into visiting malicious URLs to
exfiltrate sensitive data. Since the structure of a malicious URL evolves over time, phishing …

[HTML][HTML] A phishing-attack-detection model using natural language processing and deep learning

E Benavides-Astudillo, W Fuertes, S Sanchez-Gordon… - Applied Sciences, 2023 - mdpi.com
Phishing is a type of cyber-attack that aims to deceive users, usually using fraudulent web
pages that appear legitimate. Currently, one of the most-common ways to detect these …

[HTML][HTML] Phish responder: A hybrid machine learning approach to detect phishing and spam emails

M Dewis, T Viana - Applied System Innovation, 2022 - mdpi.com
Using technology to prevent cyber-attacks has allowed organisations to somewhat automate
cyber security. Despite solutions to aid organisations, many are susceptible to phishing and …

Enhancing phishing detection: A novel hybrid deep learning framework for cybercrime forensics

FS Alsubaei, AA Almazroi, N Ayub - IEEE Access, 2024 - ieeexplore.ieee.org
Protecting against interference is essential at a time when wireless communications are
essential for sending large amounts of data. Our research presents a novel deep learning …

Convolutional Neural Network dalam Citra Medis

D Gunawan, H Setiawan - KONSTELASI: Konvergensi Teknologi dan …, 2022 - ojs.uajy.ac.id
Penggunaan deep learning dapat diaplikasikan di berbagai bidang seperti pendidikan,
bisnis, pertanian, pertambangan, internet of things (IoT), keamanan cyber, perkiraan cuaca …

[PDF][PDF] Deep learning in phishing mitigation: a uniform resource locator-based predictive model

H Salah, H Zuhair - International Journal of Electrical and Computer …, 2023 - academia.edu
To mitigate the evolution of phish websites, various phishing prediction8 schemes are being
optimized eventually. However, the optimized methods produce gratuitous performance …

[PDF][PDF] Enhancеd Analysis Approach to Detect Phishing Attacks During COVID-19 Crisis

MT Jafar, M Al-Fawa'reh, M Barhoush… - Cybernetics and …, 2022 - intapi.sciendo.com
Public health responses to the COVID-19 pandemic since March 2020 have led to
lockdowns and social distancing in most countries around the world, with a shift from the …