Risk-based ship security analysis – a decision-support approach

The protection of shipping does not come without hazards and threats for military forces, individual civilian ship operators and crews. With particular focus on security threats, this thesis is about how to prepare for such operations without introducing unnecessary risks, i.e., supporting conscious risk-taking related to ship security. It examines both civilian and military aspects of maritime security and therefore draws from the experience of both fields. Maritime safety regulations, guidelines and methods have a history and culture of systematic research, development and implementation. In contrast, international security is highly politicised and therefore less transparent. Unfortunately, comprehensive studies of ship security risk are rare. Moreover, applying risk-based approaches to security areas requires special considerations, and the limited research in this field has led to a knowledge gap. To reduce the identified challenges with respect to security risk analysis, the goal of this thesis is to improve security decision support by defining an approach to ship security analysis. To increase overall safety, this approach must facilitate compromises between traditional maritime safety and maritime security. Accordingly, the objective is to develop an approach that is both systematic and gives the decision maker an appropriate picture of the security risks. To examine the requirements for a security decision-support approach, the work in the appended papers studies both threats to naval vessels and the security threat posed to commercial vessels by pirates. The results of the studies can be used to further develop military doctrines and civilian guidelines. This study shows that the description and quantification of the (concept of) operation in the risk analysis is central for implementing both security and naval ship survivability. In addition, the crew’s risk perception, procedural safeguards and how the implemented risk controls are perceived have an important role not only in risk analysis but also in deciding the effectiveness of implemented controls. It is also concluded that only using expected values—not collecting and using uncertainties—in the analysis can lead to misleading results. Therefore, the uncertainty treatment offered by a quantitative approach is crucial for risk understanding, especially if the aim is to find robust control options or to support the development of a resilient culture