Detecting chemical, biological, radiological and nuclear (CBRN) incidents is a high priority
task and has been a topic of intensive research for decades. Ongoing technological, data …

State-of-the-art CBRNe detection systems are predominantly available as standalone
detectors, rarely offering the potential of networking and data fusion. This paper presents a …

The increasing concerns over the use of nuclear materials for malevolent purposes (ie,
terrorist attacks) have fueled the interest in developing technologies that can detect hidden …

Datasets with accurate ground truth from unmanned aerial vehicles (UAV) are cost and time
prohibitive. This is a problem as most modern machine learning (ML) algorithms are based …

In the contemporary era, the increasing complexities in national security necessitate the
continuous evolution within the sphere of chemical, biological, radiological, and nuclear …

The nuclear power industry is currently a strategic sector in the national economy, along with
nuclear energy being considered to be an essential source of national power supply and …

Acts of cyber warfare and cyber terrorism (CWCT) that target a nation's critical infrastructure
(CI) are quickly becoming a larger threat to national security than conventional kinetic …

In this paper, we describe an approach to rank a set of terrorism-related countermeasures.
The proposed methodology is particularly useful when the set of countermeasures have to …

Water Cherenkov detectors like Super-Kamiokande, and the next generation Hyper-
Kamiokande are adding gadolinium to their water to improve the detection of neutrons. By …

The main purpose of this paper is to explore machine learning algorithms for cybersecurity
applications. No one can overemphasize the need for robust cybersecurity measures as the …