This survey paper describes a literature review of deep learning (DL) methods for cyber
security applications. A short tutorial-style description of each DL method is provided …

The scale of Internet-connected systems has increased considerably, and these systems are
being exposed to cyberattacks more than ever. The complexity and dynamics of …

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

Machine learning techniques are being widely used to develop an intrusion detection
system (IDS) for detecting and classifying cyberattacks at the network-level and the host …

Anomaly detection is an important problem that has been well-studied within diverse
research areas and application domains. The aim of this survey is two-fold, firstly we present …

With the development of the Internet, cyber-attacks are changing rapidly and the cyber
security situation is not optimistic. This survey report describes key literature surveys on …

Edge computing provides off-load computing and application services close to end-users,
greatly reducing cloud pressure and communication overhead. However, wireless edge …

This survey presents a comprehensive overview of machine learning methods for
cybersecurity intrusion detection systems, with a specific focus on recent approaches based …

With the development of the fifth‐generation networks and artificial intelligence
technologies, new threats and challenges have emerged to wireless communication system …

Malicious crowdsourcing forums are gaining traction as sources of spreading misinformation
online, but are limited by the costs of hiring and managing human workers. In this paper, we …