Since their proposal in the 2014 paper by Ian Goodfellow, there has been an explosion of
research into the area of Generative Adversarial Networks. While they have been utilised in …

Strong and efficient defences have to be developed in response to the more-sophisticated
phishing attempts is deep learning algorithms. The extensive analysis, which spans 41 …

In the digital landscape, where fake news proliferates across online platforms, it not only
distorts public discourse but also paves the way for sophisticated cyber threats, particularly …

Phishing attacks pose a significant threat to online security, utilizing fake websites to steal
sensitive user information. Deep learning techniques, particularly convolutional neural …

Phishing attacks by malicious URL/web links are common nowadays. The user data, such
as login credentials and credit card numbers can be stolen by their careless clicking on …

Security is a challenging task in terms of communication and the Internet. There are various
ways to misuse and steal users' information through the Internet, but phishing is the utmost …

The advent of internet access to people across the globe, increasing levels of connectivity,
remote employment, de-pendence on technology, and automation have presented a rapid …

The detection of malicious websites has become a critical issue in cybersecurity. Therefore,
this paper offers a comprehensive review of data-driven methods for detecting malicious …

Phishing is a social engineering attack, where an attacker poses as a legitimate individual or
institution and convinces a victim to divulge their details through human interaction. There …

Abstract Generative Adversarial Networks (GANs) are recently used to generate URL
patterns to fool the phishing URL classifiers. Some of these works use Wasserstein GAN …