The proliferation of ransomware has become a significant threat to cybersecurity in recent
years, causing significant financial, reputational, and operational damage to individuals and …

Android applications are develo** rapidly across the mobile ecosystem, but Android
malware is also emerging in an endless stream. Many researchers have studied the …

Deep Learning (DL) is a disruptive technology that has changed the landscape of cyber
security research. Deep learning models have many advantages over traditional Machine …

The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …

In the Internet age, malware (such as viruses, trojans, ransomware, and bots) has posed
serious and evolving security threats to Internet users. To protect legitimate users from these …

Security is one of the biggest challenges concerning networks and communications. The
problem becomes aggravated with the proliferation of wireless devices. Artificial Intelligence …

Most existing Android malware detection and categorization techniques are static
approaches, which suffer from evasion attacks, such as obfuscation. By analyzing program …

Despite decades of research in network traffic analysis and incredible advances in artificial
intelligence, network intrusion detection systems based on machine learning (ML) have yet …

Automated testing of Android apps is essential for app users, app developers, and market
maintainer communities alike. Given the widespread adoption of Android and the …

Malicious applications (particularly those targeting the Android platform) pose a serious
threat to developers and end-users. Numerous research efforts have been devoted to …