Monitoring the “physics” of cyber-physical systems to detect attacks is a growing area of
research. In its basic form, a security monitor creates time-series models of sensor readings …

While attacks on information systems have for most practical purposes binary outcomes
(information was manipulated/eavesdropped, or not), attacks manipulating the sensor or …

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 …

Imbalanced data learning is one of the challenging problems in data mining; among this
matter, founding the right model assessment measures is almost a primary research issue …

During the last decade, anomaly detection has attracted the attention of many researchers to
overcome the weakness of signature-based IDSs in detecting novel attacks, and …

Pattern classification systems are commonly used in adversarial applications, like biometric
authentication, network intrusion detection, and spam filtering, in which data can be …

Security metrics have received significant attention. However, they have not been
systematically explored based on the understanding of attack-defense interactions, which …

The explosive growth of the Internet of Things (IoT) applications has imposed a dramatic
increase of network data and placed a high computation complexity across various …

Vehicular networks are networks of communicating vehicles, a major enabling technology
for future cooperative and autonomous driving technologies. The most important messages …

Since the first introduction of anomaly-based intrusion detection to the research community
in 1987, the field has grown tremendously. A variety of methods and techniques introducing …