In case of a major cyber incident, organizations usually rely on external providers of Cyber Incident Response (CIR) services. CIR consultants operate in a dynamic and constantly changing environment in which they must actively engage in information management and problem solving while adapting to complex circumstances. In this challenging environment CIR consultants need to make critical decisions about what to advise clients that are impacted by a major cyber incident. Despite its relevance, CIR decision making is an understudied topic. The objective of this preliminary investigation is therefore to understand what decision-making strategies experienced CIR consultants use during challenging incidents and to offer suggestions for training and decision-aiding. A general understanding of operational decision making under pressure, uncertainty, and high stakes was established by reviewing the body of knowledge known as Naturalistic Decision Making (NDM). The general conclusion of NDM research is that experts usually make adequate decisions based on (fast) recognition of the situation and applying the most obvious (default) response pattern that has worked in similar situations in the past. In exceptional situations, however, this way of recognition-primed decision-making results in suboptimal decisions as experts are likely to miss conflicting cues once the situation is quickly recognized under pressure. Understanding the default response pattern and the rare occasions in which this response pattern could be ineffective is therefore key for improving and aiding cyber incident response decision making. Therefore, we interviewed six experienced CIR consultants and used the critical decision method (CDM) to learn how they made decisions under challenging conditions. The main conclusion is that the default response pattern for CIR consultants during cyber breaches is to reduce uncertainty as much as possible by gathering and investigating data and thus delay decision making about eradication until the investigation is completed. According to the respondents, this strategy usually works well and provides the most assurance that the threat actor can be completely removed from the network. However, the majority of respondents could recall at least one case in which this strategy (in hindsight) resulted in unnecessary theft of data or damage. Interestingly, this finding is strikingly different from other operational decision-making domains such as the military, police and fire service in which there is a general tendency to act rapidly instead of searching for more information. The main advice is that training and decision aiding of (novice) cyber incident responders should be aimed at the following: (a) make cyber incident responders aware of how recognition-primed decision making works; (b) discuss the default response strategy that typically works well in several scenarios; (c) explain the exception and how the exception can be recognized; (d) provide alternative response strategies that work better in exceptional situations.
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Lessons learned on the progress towards 4th generation district heating (4DHC) are presented from 6 pilot implementation projects in the UK, Ireland, Belgium, France, and the Netherlands (HeatNet project). The pilots have implemented the infrastructure for district heating from various (waste) heat and renewable sources to reduce CO2 emissions. With the development of long term road maps, progress is made towards the role out of 4DHC in the regions. The pilots have a different level of experience with district heating and transnational learning is specifically addressed. Purpose of the evaluation of the pilots is to give local authorities insight into barriers and solutions and the way they are closely linked to stakeholders in their geographical, politicaland cultural context in NWE. To do this, the financial, regulatory and organisational barriers the pilots face and possible solutions that were shared between the pilots are analysed in the context of system innovation. Differences in national and regional contexts have been analysed to be able to generalise solutions to a level they can be used in a different context. We will confront the pilot’s development with best and worst practice from literature and score Key Success Factors.
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