Multi-Purpose Cyber Environment for Maritime Sector

The cyber attack surface in a maritime environment is constantly growing. More current information and computer technologies are being used on cargo and passenger ships to save on operational costs and increase navigational safety. Along with the growing reliance on automation, the risk of a disruption to a vessel's critical systems by drawing on the wrong inputs from sensors to change the behaviour of the actuators has significantly increased. Traditional operational technological systems are much more complicated to update than the automatic software updates we see in information technology systems. To better understand existing cyber threats in the maritime sector and increase cybersecurity resilience, this paper aims to replicate the digital components of a ship's bridge to examine scenarios when the bridge system loses connectivity, receives the wrong inputs from sensors, or the internal system becomes compromised. The simulator differentiates fundamentally from traditional simulators or digital twins in the maritime sector that focus on training seafarers. This environment generates data streams that are similar to those on board a ship. Those data streams can be analysed, modified and spoofed to observe the effects. The effects can be technical but it is equally necessary to analyse how human beings would react in specific circumstances. Our work provides the opportunity to isolate the ship network traffic, conduct penetration testing, find cybersecurity vulnerabilities on devices, and execute cyber attacks without the dangers associated with running such scenarios on a vessel in the open sea.</jats:p

Minimal number of chromatographic test parameters for the characterisation of reversed-phase liquid chromatographic stationary phases

This paper focuses on the classification or differentiation of RP-HPLC columns based on measured chromatographic properties. A chemometric study has been conducted on a published data set consisting of 85 RP-HPLC columns and on a data set consisting of 47 self-tested columns. Principal component analysis enables determination of the number of parameters necessary for a rational differentiation. The results show that reducing the number of parameters for such differentiation still allows classification of the columns just as a higher number did. It is shown that three test parameters produce a classification similar to that obtained with five parameters</p

Characterisation of reversed-phase liquid chromatographic columns by chromatographic tests. Evaluation of 36 test parameters: repeatability, reproducibility and correlation

The European Pharmacopoeia (Ph. Eur.) or other official compendia give only a general description of the stationary phase in the description of a liquid chromatographic method. Therefore the selection of a column giving suitable selectivity presents difficulties. Earlier, a test procedure was proposed that allows measurement of a number of parameters which are reported to be representative for stationary phase characteristics. This paper describes how the test procedure was applied on 69 RP-LC C18 columns. Chromatographic parameters obtained as test results were evaluated, and their repeatability, reproducibility and correlation were examined</p

Characterisation of reversed-phase liquid chromatographic columns by chromatographic tests. Rational column classification by a minimal number of column test parameters

The European Pharmacopoeia (Ph. Eur.) and other official compendia give only a general description of the stationary phase in the description of a liquid chromatographic method. Therefore the selection of a column giving suitable selectivity presents difficulties. Earlier, a test procedure was proposed that allows to measure 36 chromatographic parameters which have been described for characterising stationary phases. This procedure was carried out on 69 reversed-phase liquid chromatography (RP-LC) columns. This paper focuses on the classification of RP-LC stationary phases based on chromatographic parameters. A chemometric study was conducted using 24 parameters that could be measured in a repeatable and reproducible way. Principal component analysis was used to classify the columns and to estimate the minimal number of parameters necessary for a rational classification. It is shown that after reducing the number of parameters from 24 to four or three, similar classifications were obtained. The column classifications were compared to the European Pharmacopoeia stationary phase description and to the column properties obtained from the manufacturers</p