The continuous proliferation of malware poses a formidable threat to the cyberspace
landscape. Researchers have proffered a multitude of sophisticated defense mechanisms …

This paper proposes an AI-powered intrusion detection method that improves intrusion
detection performance by increasing the quality of the training set and employing numerous …

IoT malware analysis is crucial for understanding the behavior and purpose of malware
samples. While deep learning methods have been applied to IoT malware analysis using …

With the popularity of electronic devices, the number of malware has increased dramatically,
posing a serious threat to the digital world. Accurately identifying malware has become a …

With the popularization of computer technology, the number of malware has increased
dramatically in recent years. Some malware can threaten the network security of users by …

To mitigate the evolution of phish websites, various phishing prediction8 schemes are being
optimized eventually. However, the optimized methods produce gratuitous performance …

Abstract Smart Autonomous Vehicles (AVSs) are networks of Cyber-Physical Systems
(CPSs) in which they wirelessly communicate with other CPSs sub-systems (eg, smart …

In contemporary times, the landscape of malware analysis has advanced into an era of
sophisticated threat detection. Today's malware sandboxes not only conduct rudimentary …

While users tend to perceive instructional videos as an experience rather than a lesson with
a set of instructions, instructional videos are more effective and appealing than textual user …

In dynamic Windows malware detection, deep learning models are extensively deployed to
analyze API sequences. Methods based on API sequences play a crucial role in malware …