Dataset Information

Simulations in Cyber-Security: A Review of Cognitive Modeling of Network Attackers, Defenders, and Users.

ABSTRACT: Computational models of cognitive processes may be employed in cyber-security tools, experiments, and simulations to address human agency and effective decision-making in keeping computational networks secure. Cognitive modeling can addresses multi-disciplinary cyber-security challenges requiring cross-cutting approaches over the human and computational sciences such as the following: (a) adversarial reasoning and behavioral game theory to predict attacker subjective utilities and decision likelihood distributions, (b) human factors of cyber tools to address human system integration challenges, estimation of defender cognitive states, and opportunities for automation, (c) dynamic simulations involving attacker, defender, and user models to enhance studies of cyber epidemiology and cyber hygiene, and (d) training effectiveness research and training scenarios to address human cyber-security performance, maturation of cyber-security skill sets, and effective decision-making. Models may be initially constructed at the group-level based on mean tendencies of each subject's subgroup, based on known statistics such as specific skill proficiencies, demographic characteristics, and cultural factors. For more precise and accurate predictions, cognitive models may be fine-tuned to each individual attacker, defender, or user profile, and updated over time (based on recorded behavior) via techniques such as model tracing and dynamic parameter fitting.

SUBMITTER: Veksler VD

PROVIDER: S-EPMC5967149 | biostudies-other | 2018

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Simulations in Cyber-Security: A Review of Cognitive Modeling of Network Attackers, Defenders, and Users.

Veksler Vladislav D VD Buchler Norbou N Hoffman Blaine E BE Cassenti Daniel N DN Sample Char C Sugrim Shridat S

Frontiers in psychology 20180515

Computational models of cognitive processes may be employed in cyber-security tools, experiments, and simulations to address human agency and effective decision-making in keeping computational networks secure. Cognitive modeling can addresses multi-disciplinary cyber-security challenges requiring cross-cutting approaches over the human and computational sciences such as the following: (a) adversarial reasoning and behavioral game theory to predict attacker subjective utilities and decision likel ...[more]

PMID: 29867661

Similar Datasets

Project description:A critical requirement for developing a cyber capable workforce is to understand how to challenge, assess, and rapidly develop human cyber skill-sets in realistic cyber operational environments. Fortunately, cyber team competitions make use of simulated operational environments with scoring criteria of task performance that objectively define overall team effectiveness, thus providing the means and context for observation and analysis of cyber teaming. Such competitions allow researchers to address the key determinants that make a cyber defense team more or less effective in responding to and mitigating cyber attacks. For this purpose, we analyzed data collected at the 12th annual Mid-Atlantic Collegiate Cyber Defense Competition (MACCDC, http://www.maccdc.org), where eight teams were evaluated along four independent scoring dimensions: maintaining services, incident response, scenario injects, and thwarting adversarial activities. Data collected from the 13-point OAT (Observational Assessment of Teamwork) instrument by embedded observers and a cyber teamwork survey completed by all participants were used to assess teamwork and leadership behaviors and team composition and work processes, respectively. The scores from the competition were used as an outcome measure in our analysis to extract key features of team process, structure, leadership, and skill-sets in relation to effective cyber defense. We used Bayesian regression to relate scored performance during the competition to team skill composition, team experience level, and an observational construct of team collaboration. Our results indicate that effective collaboration, experience, and functional role-specialization within the teams are important factors that determine the success of these teams in the competition and are important observational predictors of the timely detection and effective mitigation of ongoing cyber attacks. These results support theories of team maturation and the development of functional team cognition applied to mastering cybersecurity.

Dataset Information

Simulations in Cyber-Security: A Review of Cognitive Modeling of Network Attackers, Defenders, and Users.

Publications

Simulations in Cyber-Security: A Review of Cognitive Modeling of Network Attackers, Defenders, and Users.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets