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[HTML][HTML] A systematic review on deep-learning-based phishing email detection
Phishing attacks are a growing concern for individuals and organizations alike, with the
potential to cause significant financial and reputational damage. Traditional methods for …
potential to cause significant financial and reputational damage. Traditional methods for …
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
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 …
[HTML][HTML] HCRNNIDS: Hybrid convolutional recurrent neural network-based network intrusion detection system
Nowadays, network attacks are the most crucial problem of modern society. All networks,
from small to large, are vulnerable to network threats. An intrusion detection (ID) system is …
from small to large, are vulnerable to network threats. An intrusion detection (ID) system is …
Deep cybersecurity: a comprehensive overview from neural network and deep learning perspective
Deep learning, which is originated from an artificial neural network (ANN), is one of the
major technologies of today's smart cybersecurity systems or policies to function in an …
major technologies of today's smart cybersecurity systems or policies to function in an …
Applications of deep learning for phishing detection: a systematic literature review
Phishing attacks aim to steal confidential information using sophisticated methods,
techniques, and tools such as phishing through content injection, social engineering, online …
techniques, and tools such as phishing through content injection, social engineering, online …
Multi‐aspects AI‐based modeling and adversarial learning for cybersecurity intelligence and robustness: A comprehensive overview
Due to the rising dependency on digital technology, cybersecurity has emerged as a more
prominent field of research and application that typically focuses on securing devices …
prominent field of research and application that typically focuses on securing devices …
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 …
[HTML][HTML] A deep learning-based innovative technique for phishing detection in modern security with uniform resource locators
Organizations and individuals worldwide are becoming increasingly vulnerable to
cyberattacks as phishing continues to grow and the number of phishing websites grows. As …
cyberattacks as phishing continues to grow and the number of phishing websites grows. As …
Deep learning applications in manufacturing operations: a review of trends and ways forward
Purpose Deep learning (DL) technologies assist manufacturers to manage their business
operations. This research aims to present state-of-the-art insights on the trends and ways …
operations. This research aims to present state-of-the-art insights on the trends and ways …