While Digital Twins (DTs) bring convenience to city managers, they also generate new
challenges to city network security. Currently, cyberspace security becomes increasingly …

This work aims to analyze malicious communication behaviors that pose a threat to the
security of digital twins (DTs) and safeguard user privacy. A unified and integrated …

Abstract Nowadays, many Internet of Things (IoT) devices of different types are used in
creating smart applications like smart cities, smart industries, smart environments, and the …

In recent past years, Deep Learning presented an excellent performance in different areas
like image recognition, pattern matching, and even in cybersecurity. The Deep Learning has …

Digital twin (DT) technologies have emerged as a solution for real-time data-driven
modeling of cyber physical systems (CPS) using the vast amount of data available by …

Internet-of-Things (IoT) technology is increasingly prominent in the current stage of social
development. All walks of life have begun to implement the IoT integration technology, so as …

This paper presents an exploratory machine learning attack based on deep learning to infer
the functionality of an arbitrary classifier by polling it as a black box, and using returned …

The legacy security defense mechanisms cannot resist where emerging sophisticated
threats such as zero-day and malware campaigns have profoundly changed the dimensions …

As a national critical infrastructure, the smart grid has attracted widespread attention for its
cybersecurity issues. The development towards an intelligent, digital, and Internetconnected …

Benefiting from the advancement of algorithms in massive data and powerful computing
resources, deep learning has been explored in a wide variety of fields and produced …