Container vessels arriving in a port before or after their scheduled time can cause problems in the container terminal planning and planning of hinterland transportation. This in turn leads to an increase of the costs in the supply chain. Vessels communicate their Estimated Time of Arrival via Automatic Idetification System(AIS) data to the port. This arrival time is estimated by the crew of the vessel and manually inputted into the AIS. In this research a proof of concept is shown that the Estimated Time of Arrival (ETA) prediction of container vessels can be improved. Vessels en route to the Port of Rotterdam are used as a case study. Different frameworks and algorithms are introduced to improve the data quality of AIS messages, to identify a set of possible routes and to do predictions based on the set of possible routes. It is possible to do predictions based on pre-processed AIS messages and a set of possible routes that perform at the same level as the best guess of a vessel’s crew.

Currently, DDoS attacks have become inevitable for financial services and their threat keeps rising. Numerous researches have focused on the technical since the rise of DDoS amplification attacks. However, there is less understanding regarding their target selection on financial services. This research uses a mixed method approach to capture factors that influence cybercriminals in their selection of victims. Via data from amplification DDoS honeypots, various factors are identified and explanatory models are provided. In addition, financial cyber security experts are consulted to assess their perspective on target selection. The analysis demonstrates that certain countries have significantly higher or lower victims, which can partially be explained through country level factors such as the ICT development and Normal GDP Per capita. In addition, the ICT development influences the duration of the attack significantly. The findings also indicate that organizational size, as measured by market value, showed a limited effect on the number of attacks. Contrary, experts regarded the size as a highly influential factor. The analyses furthermore demonstrate that financial organisations incur significantly more attacks on Friday than on any other day. Moreover, the experts mention additional target selection factors such as,
reputation, media attention, patching, having capable employees, and mitigation parties. Finally, this paper reflects on the implications of these findings for the financial sector and related sectors.