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This report summarizes the discussions and findings of the 2017 North Atlantic Treaty Organization (NATO) Workshop, IST-153, on Cyber Resilience, held in Munich, Germany, on 23-25 October 2017, at the University of Bundeswehr. Despite continual progress in managing risks in the cyber domain, anticipation and prevention of all possible attacks and malfunctions are not feasible for the current or future systems comprising the cyber infrastructure. Therefore, interest in cyber resilience (as opposed to merely risk-based approaches) is increasing rapidly, in literature and in practice. Unlike concepts of risk or robustness - which are often and incorrectly conflated with resilience - resiliency refers to the system's ability to recover or regenerate its performance to a sufficient level after an unexpected impact produces a degradation of its performance. The exact relation among resilience, risk, and robustness has not been well articulated technically. The presentations and discussions at the workshop yielded this report. It focuses on the following topics that the participants of the workshop saw as particularly important: fundamental properties of cyber resilience; approaches to measuring and modeling cyber resilience; mission modeling for cyber resilience; systems engineering for cyber resilience, and dynamic defense as a path toward cyber resilience.

This report summarizes the discussions and findings of the Workshop on Intelligent Autonomous Agents for Cyber Defence and Resilience organized by the NATO research group IST-152-RTG. The workshop was held in Prague, Czech Republic, on 18-20 October 2017. There is a growing recognition that future cyber defense should involve extensive use of partially autonomous agents that actively patrol the friendly network, and detect and react to hostile activities rapidly (far faster than human reaction time), before the hostile malware is able to inflict major damage, evade friendly agents, or destroy friendly agents. This requires cyber-defense agents with a significant degree of intelligence, autonomy, self-learning, and adaptability. The report focuses on the following questions: In what computing and tactical environments would such an agent operate? What data would be available for the agent to observe or ingest? What actions would the agent be able to take? How would such an agent plan a complex course of actions? Would the agent learn from its experiences, and how? How would the agent collaborate with humans? How can we ensure that the agent will not take undesirable destructive actions? Is it possible to help envision such an agent with a simple example?

There is an obvious need for a valid, realistic model for research on the occupational needs of the community for relevant time periods to provide planners with quantified data on which to base decisions. The purpose of this study is to develop a statewide system to: (1) identify job needs at the local community level, and (2) relate job needs to training programs in the educational system. The assessment of both urban and rural community needs is difficult to derive. This model focuses on the local community, and that community's educational training system, as opposed to many other models which focus on the state or national level. Basic data sources that appear most useful in occupational needs assessments are Florida Department of Commerce quarterly employment reports, Bureau of Labor Statistics labor market trends, local Florida State Employment Service offices Job Bank data, and the U.S. Labor Department Manpower Administration forecasting documentation. This model is of interest not only to educators and manpower specialists, but also to any planner who is concerned either with the supply of trained persons or demand for training services. (Author/AH)

It is the intent of the occupational needs assessment model to provide data on present and future occupational training requirements for local communities, place the job skill needs in a priority ranking, and relate the occupational need data to the labor market and educational curriculum. This paper shows the development of this model, indicating how data sources flow into the model to relate the job market demand to training needs for the community, and specifying the data gathering activities for implementing the model. A comprehensive evaluation program with an accurate needs assessment process behind it can be an effective instrument of change within the college and within the community. (Author/AH)