This article explores deep learning models in the field of malware detection in cyberspace,
aiming to provide insights into their relevance and contributions. The primary objective of the …

With the growing popularity of autonomous vehicles (AVs), confirming their safety has
become a significant concern. Vehicle manufacturers have combined the Android operating …

the paper discusses a way of growing the capability of severe deep learning machines
(ELM) for biomedical informatics programs. This technique involves varying the dimensions …

The proliferation of Android applications and their extensive adoption within the smartphone
sector has contributed to an upsurge in malware infiltration and exploitation. Vulnerabilities …

The increasing ubiquity of Android devices has precipitated a concomitant surge in
sophisticated malware attacks, posing critical challenges to cybersecurity infrastructures …

With the fast growth of mobile phone usage, malicious threats against Android mobile
devices are enhanced. The Android system utilizes a wide range of sensitive apps like …

The multicollinearity problem is a common phenomenon in data-driven studies, significantly
affecting the performance of machine learning algorithms during the process of extracting …

With the increasing popularity of Android smartphones, malware targeting the Android
platform is showing explosive growth. Currently, mainstream detection methods use static …

Securing Android apps presents a formidable challenge due to the incessant threat of
malicious applications. Traditional solutions have grown less effective in the face of the vast …

Malicious software (malware) analysis and classification has obtained a greater
development in the systems connected by the Internet. The malware accomplishes the …