Supporting detection of hostile intentions: automated assistance in a dynamic decision-making context

In a dynamic decision-making task simulating basic ship movements, participants attempted, through a series of actions, to elicit and identify which one of six other ships was exhibiting either of two hostile behaviors. A high-performing, although imperfect, automated attention aid was introduced. It visually highlighted the ship categorized by an algorithm as the most likely to be hostile. Half of participants also received automation transparency in the form of a statement about why the hostile ship was highlighted. Results indicated that while the aid's advice was often complied with and hence led to higher accuracy with a shorter response time, detection was still suboptimal. Additionally, transparency had limited impacts on all aspects of performance. Implications for detection of hostile intentions and the challenges of supporting dynamic decision making are discussed.

The Human Factors of Cyber Network Defense

Technology’s role in the fight against malicious cyber-attacks is critical to the increasingly networked world of today. Yet, technology does not exist in isolation: the human factor is an aspect of cyber-defense operations with increasingly recognized importance. Thus, the human factors community has a unique responsibility to help create and validate cyber defense systems according to basic principles and design philosophy. Concurrently, the collective science must advance. These goals are not mutually exclusive pursuits: therefore, toward both these ends, this research provides cyber-cognitive links between cyber defense challenges and major human factors and ergonomics (HFE) research areas that offer solutions and instructive paths forward. In each area, there exist cyber research opportunities and realms of core HFE science for exploration. We raise the cyber defense domain up to the HFE community at-large as a sprawling area for scientific discovery and contribution.