Cybercriminals are becoming increasingly intelligent and aggressive, making them more
adept at covering their tracks, and the global epidemic of cybercrime necessitates significant …

With continuous advancement of technology, the frequency of malware injection attacks has
risen, posing significant risks to the security of computer systems and networks. This …

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 …

Conventional malware detection approaches have the overhead of feature extraction, the
requirement of domain experts, and are time-consuming and resource-intensive. Learning …

In the rapidly advancing field of Artificial Intelligence (AI), this study presents a critical
evaluation of the resilience and cybersecurity efficacy of leading AI models, including …

The presence of malicious software (malware), for example, in Android applications (apps),
has harmful or irreparable consequences to the user and/or the device. Despite the …

Cyber threats continue to evolve in complexity, thereby traditional cyber threat intelligence
(CTI) methods struggle to keep pace. AI offers a potential solution, automating and …

Rootkits are malicious programs designed to conceal their activities on compromised
systems, making them challenging to detect using conventional methods. As the threat …

The tremendous growth of the Internet of Things (IoT) has gained a lot of attention in the
global market. The massive deployment of IoT is also inherent in various security …

The introduction of transformers has been an important breakthrough for AI research and
application as transformers are the foundation behind Generative AI. A promising …