Cybercrime is estimated to have cost the global economy just under USD 1 trillion in 2020,
indicating an increase of more than 50% since 2018. With the average cyber insurance …

People in the modern era spend most of their lives in virtual environments that offer a range
of public and private services and social platforms. Therefore, these environments need to …

Malware detection approaches can be classified into two classes, including static analysis
and dynamic analysis. Conventional approaches of the two classes have their respective …

Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …

Nowadays, Artificial Intelligence (AI) is widely applied in every area of human being's daily
life. Despite the AI benefits, its application suffers from the opacity of complex internal …

Malware is constantly evolving with rising concern for cyberspace. Deep learning-based
malware detectors are being used as a potential solution. However, these detectors are …

This paper delves into the transformative role of machine learning (ML) techniques in
revolutionizing the security of electric and flying vehicles (EnFVs). By exploring key domains …

Inspired by biological neurons, the activation functions play an essential part in the learning
process of any artificial neural network (ANN) commonly used in many real-world problems …

Abstract 'Curse of dimensionality'and the trade-off between low false alarm rate and high
detection rate are the major concerns while designing an efficient intrusion detection system …

This research introduces a theoretical framework for network anomaly detection in
cybersecurity, emphasizing the integration of adaptive machine learning models, ensemble …