The convolutional neural network (CNN)-based models have achieved tremendous breakthroughs in many end-to-end applications, such as image identification, text classification, and speech recognition.

Mobile phones have evolved into powerful handheld computers, fostering a vast application ecosystem but also increasing security and privacy risks. Traditional deep learning-based Android malware ...

Millions of low-cost devices for media streaming, in-vehicle entertainment, and video projection are infected with malware that turns consumer networks into platforms for distributing malware ...

As scam detection features for calls and texts get more sophisticated, so too do the threats designed to evade such measures. Android users are being targeted with malware that can create fake ...

The rapid increase in smartphone usage has led to a corresponding rise in malicious Android applications, making it important to develop efficient and sustainable malware detection methods that ...

The latest version of the 'Crocodilus' Android malware has introduced a new mechanism that adds a fake contact on the infected device's contact list to deceive victims.

Semi-supervised change detection (SSCD) has become increasingly important in remote sensing image (RSI) analysis due to the scarcity of labeled data. While state-of-the-art SSCD methods have achieved ...

The term "malicious software" (or "Malware") refers to any software designed specifically to cause harm to a computer system. Malware has also progressed in its ability to avoid detection and launch ...