Anomaly detection is concerned with identifying data patterns that deviate remarkably from
the expected behavior. This is an important research problem, due to its broad set of …

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

Abstract Denial of Service and Distributed Denial of Service (DoS/DDoS) attacks have been
one of the biggest threats against communication networks and applications throughout the …

Software-defined networking (SDN) has become a promising trend for managing the
Industrial Internet of Things (IIoT) devices. As the core of sensitive data storage and …

Advanced persistent threats (APTs) are one of today's major threats to cyber security. Highly
determined attackers along with novel and evasive exfiltration techniques mean APT attacks …

In heterogeneous Internet of Things (IoT) networks, various communication technologies
lead to different transmission ranges of nodes, and they can cooperatively provide seamless …

This work examines propagation of cyber-threats over networks under an adversarial
formulation. Exploiting Kendall's birth-death-immigration model, we propose an analytical …

In this paper, we consider a novel-ary sequential hypothesis testing problem in which an
adversary is present and perturbs the distributions of the samples before the decision maker …

The main goal of this work is to propose a novel compartmental SEA (Susceptible–Exposed–
Attacked) model to simulate malware spreading on an IoT (Internet of Things) network. This …

The development of cyber-assured systems is a challenging task, particularly due to the cost
and complexities associated with the modern hybrid networks architectures, as well as the …