Zero-day malware is malware that has never been seen before or is so new that no anti-
malware software can catch it. This novelty and the lack of existing mitigation strategies …

Abstract Detecting attacks to Cyber-Physical Systems (CPSs) is of utmost importance, due to
their increasingly frequent use in many critical assets. Intrusion detection in CPSs and other …

The fourth industrial revolution is marked by the rapid growth of Internet of Things (IoT)
technology, leading to an increase in the number of IoT devices. Unfortunately, this also …

Malware authors apply different techniques of control flow obfuscation, in order to create
new malware variants to avoid detection. Existing Siamese neural network (SNN)-based …

Abstract Software Defined Networks (SDN) is a new emerging networking architecture
facilitated by a separate controller. It has a centralized architecture that serves network …

The growing sophistication, frequency and severity of cyberattacks targeting all sectors
highlight their inevitability and the impossibility of completely protecting the integrity of …

Abstract Machine Learning techniques for network-based intrusion detection are widely
adopted in the scientific literature. Besides being highly variable, network traffic behavior …

Anomaly-based intrusion detectors are machine learners trained to distinguish between
normal and anomalous data. The normal data is generally easy to collect when building the …

The number of papers on network intrusion detection based on machine and deep learning
is growing at an unprecedented rate. Most of these papers follow a well-consolidated …

With the growing processing power of computing systems and the increasing availability of
massive datasets, machine learning algorithms have led to major breakthroughs in many …