In this work, we developed a QSAR model using the K-Nearest Neighbor (KNN) algorithm to
predict the corrosion inhibition performance of the inhibitor compound. To overcome the …

The increased adoption of cloud computing resources produces major loopholes in cloud
computing for cybersecurity attacks. An intrusion detection system (IDS) is one of the vital …

Advancement of the Internet has increased security risks associated with data protection and
online shop**. Several techniques compromise Internet security, including hacking, SQL …

Phishing is a type of online scam where the attacker tries to trick you into giving away your
personal information, such as passwords or credit card details, by posing as a trustworthy …

This Machine-learning-based phishing detection employs statistical models and algorithms
to assess and recognise phishing attacks. These algorithms can learn patterns and features …

In the evolving landscape of cyber threats, phishing attacks pose significant challenges,
particularly through deceptive webpages designed to extract sensitive information under the …

The detection of phishing websites based on machine learning has gained much attention
due to its ability to detect newly generated phishing URLs. To detect phishing websites, most …

The rapid evolution of internet technologies has led to a significant proliferation of connected
devices, expanding the potential attack surface. This necessitates the implementation of …

The first and foremost task of a phishing-detection mechanism is to confirm the appearance
of a suspicious page that is similar to a genuine site. Once this is found, a suitable URL …

Many existing studies on neural network accuracy utilize datasets that may not always reflect
real-world conditions. While it has been demonstrated that accuracy tends to decrease as …