This thesis is motivated by the goals of understanding in depth which information security value aspects are relevant in real-world business environments and contributing a value-prioritised information security investment decision model suitable for practitioners in the field. Pursuing this goal, we apply a mixed method research approach that combines the analysis of the relevant literature, expert interviews, practitioner survey data and structural equation modelling and multicriteria decision analysis. In the first step, we address the identified terminology gap to clarify the meaning of ‘cyber security’ by analysing authoritative definition sources in the literature and presenting an improved definition distinct from that of ‘information security’. We then investigate the influence of repeated information security breaches on an organisation’s stock market value to benchmark the wider economic impact of such events. We find abnormal returns following a breach event as well as weak statistical significance on abnormal returns for later breach events, confirming that data breaches have a negative impact on organisations. To understand how security practitioners view this topic, we conduct and analyse semi-structured interviews following a grounded theory approach. Our research identifies 15 principles aligned with a conceptual information security investment framework. The key components of this framework such as the business environment, drivers (threat landscape, legal and regulatory) and challenges (cost of security, uncertainty) are found to be a crucial part of value-prioritised information security investment decisions. We verify these findings through a structural model consisting of five latent variables representing key areas in value-focused information security investment decisions. The model shows that security capabilities have the largest direct effect on the value organisations gain from information security investment. In addition, the value outcome is strongly influenced by organisation-specific constructs such as the threat landscape and regulatory requirements, which must therefore be considered when creating security capabilities. By addressing one of the key uncertainty issues, we use a probabilistic topic modelling approach to identify latent security threat prediction topics from a large pool of security predictions publicised in the media. We further verify the prediction outcomes through a survey instrument. The results confirm the feasibility of forecasting notable threat developments in this context, implying that practitioners can use this approach to reduce uncertainty and improve security investment decisions. In the last part of the thesis, we present a multicriteria decision model that combines our results on value-prioritised information security investments in an organisational context. Based on predefined criteria and preferences and by utilising stochastic multicriteria acceptability analysis as the adopted methodology, our model can deal with substantial uncertainty while offering ease of use for practitioners
