The integration of deep learning models into intelligent infrastructure systems presents
significant opportunities for enhancing efficiency, safety, and resilience in urban …

It has become essential to protect vital infrastructures from cyber threats in an age where
technology permeates every aspect of our lives. This article examines how machine learning …

Deep learning techniques have been widely adopted for cyber defence applications such as
malware detection and anomaly detection. The ever-changing nature of cyber threats has …

Technology is shaping our lives in a multitude of ways. This is fuelled by a technology
infrastructure, both legacy and state of the art, composed of a heterogeneous group of …

In recent years, deep learning (DL) models have attracted widespread concern. Due to its
own characteristics, DL has been successfully applied in the fields of object detection …

As network security threats continue to evolve in complexity and sophistication, there is a
growing need for advanced solutions to enhance network security and threat detection …

The proliferation of artificial intelligence and edge computing has led to an increase in the
deployment of proprietary deep learning models on third-party edge servers or devices to …

As computer performance advances and deep learning models proliferate, their applications
expand, but concerns arise due to their opaque nature and security issues. Edge …

Deep learning frameworks promote the development of artificial intelligence and
demonstrate considerable potential in numerous applications. However, the security issues …

Rapid technological improvements have brought significant hazards to sensitive data and
information. Cyberspace has connected various data structures, ranging from private …