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Industry standard frameworks are now widespread for labeling the high-levelstages and granular actions of attacker and defender behavior in cyberspace.While these labels are used for atomic actions, and to some extent forsequences of actions, there remains a need for labeled data from realisticfull-scale attacks. This data is valuable for better understanding humanactors' decisions, behaviors, and individual attributes. The analysis couldlead to more effective attribution and disruption of attackers.  We present a methodological approach and exploratory case study forsystematically analyzing human behavior during a cyber offense/defensecapture-the-flag (CTF) game. We describe the data collection and analysis toderive a metric called keystroke accuracy. After collecting players' commands,we label them using the MITRE ATT&CK framework using a new tool calledPathfinder. We present results from preliminary analysis of participants'keystroke accuracy and its relation to score outcome in CTF games. We describefrequency of action classification within the MITRE ATT&CK framework anddiscuss some of the mathematical trends suggested by our observations. Weconclude with a discussion of extensions for the methodology, includingperformance evaluation during games and the potential use of this methodologyfor training artificial intelligence.

Battle Ground: Data Collection and Labeling of CTF Games to Understand Human Cyber Operators