A survey on deep learning for cybersecurity: Progress, challenges, and opportunities
As the number of Internet-connected systems rises, cyber analysts find it increasingly difficult
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …
Deep learning for phishing detection: Taxonomy, current challenges and future directions
Phishing has become an increasing concern and captured the attention of end-users as well
as security experts. Existing phishing detection techniques still suffer from the deficiency in …
as security experts. Existing phishing detection techniques still suffer from the deficiency in …
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 …
There are numerous ways to harm the security of internet users; the most common is …
An effective phishing detection model based on character level convolutional neural network from URL
Phishing is the easiest way to use cybercrime with the aim of enticing people to give
accurate information such as account IDs, bank details, and passwords. This type of …
accurate information such as account IDs, bank details, and passwords. This type of …
A survey of intelligent detection designs of HTML URL phishing attacks
Phishing attacks are a type of cybercrime that has grown in recent years. It is part of social
engineering attacks where an attacker deceives users by sending fake messages using …
engineering attacks where an attacker deceives users by sending fake messages using …
Phishing or not phishing? A survey on the detection of phishing websites
R Zieni, L Massari, MC Calzarossa - IEEE Access, 2023 - ieeexplore.ieee.org
Phishing is a security threat with serious effects on individuals as well as on the targeted
brands. Although this threat has been around for quite a long time, it is still very active and …
brands. Although this threat has been around for quite a long time, it is still very active and …
A hybrid DNN–LSTM model for detecting phishing URLs
Phishing is an attack targeting to imitate the official websites of corporations such as banks,
e-commerce, financial institutions, and governmental institutions. Phishing websites aim to …
e-commerce, financial institutions, and governmental institutions. Phishing websites aim to …
Web phishing detection using web crawling, cloud infrastructure and deep learning framework
The pandemic of COVID-19 obliges citizens to follow the “work from home “scheme. The
Internet is also a powerful channel for social connections. The huge dependency of people …
Internet is also a powerful channel for social connections. The huge dependency of people …
An investigation into the performances of the Current state-of-the-art Naive Bayes, Non-Bayesian and Deep Learning Based Classifier for Phishing Detection: A …
Phishing is one of the most effective ways in which cybercriminals get sensitive details such
as credentials for online banking, digital wallets, state secrets, and many more from potential …
as credentials for online banking, digital wallets, state secrets, and many more from potential …
CNN-Fusion: An effective and lightweight phishing detection method based on multi-variant ConvNet
Phishing scams are increasing as the technical skills and costs of phishing attacks diminish,
emphasizing the need for rapid, precise, and low-cost prevention measures. Based on a …
emphasizing the need for rapid, precise, and low-cost prevention measures. Based on a …