Deep Learning (DL) is a disruptive technology that has changed the landscape of cyber
security research. Deep learning models have many advantages over traditional Machine …

Blockchain technology can be extensively applied in diverse services, including online
micro-payments, supply chain tracking, digital forensics, health-care record sharing, and …

With the booming of cyber attacks and cyber criminals against cyber-physical systems
(CPSs), detecting these attacks remains challenging. It might be the worst of times, but it …

The constantly increasing number of disclosed security vulnerabilities have become an
important concern in the software industry and in the field of cybersecurity, suggesting that …

Traffic analysis is a compound of strategies intended to find relationships, patterns,
anomalies, and misconfigurations, among others things, in Internet traffic. In particular, traffic …

While machine learning and artificial intelligence have long been applied in networking
research, the bulk of such works has focused on supervised learning. Recently, there has …

Driven by the increasing scale and high profile cybersecurity incidents related public data,
recent years we have witnessed a paradigm shift in understanding and defending against …

Abstract Machine Learning (ML) techniques are becoming an invaluable support for network
intrusion detection, especially in revealing anomalous flows, which often hide cyber-threats …

Information communications technology systems are facing an increasing number of cyber
security threats, the majority of which are originated by insiders. As insiders reside behind …

Identifying the type of a network flow or a specific application has many advantages, such
as, traffic engineering, or to detect and prevent application or application types that violate …