Information-Pooling Bias in Collaborative Security Incident Correlation Analysis

Objective: Incident correlation is a vital step in the cybersecurity threat detection process. This article presents research on the effect of group-level information-pooling bias on collaborative incident correlation analysis in a synthetic task environment. Background: Past research has shown that uneven information distribution biases people to share information that is known to most team members and prevents them from sharing any unique information available with them. The effect of such biases on security team collaborations are largely unknown. Method: Thirty 3-person teams performed two threat detection missions involving information sharing and correlating security incidents. Incidents were predistributed to each person in the team based on the hidden profile paradigm. Participant teams, randomly assigned to three experimental groups, used different collaboration aids during Mission 2. Results: Communication analysis revealed that participant teams were 3 times more likely to discuss security incidents commonly known to the majority. Unaided team collaboration was inefficient in finding associations between security incidents uniquely available to each member of the team. Visualizations that augment perceptual processing and recognition memory were found to mitigate the bias. Conclusion: The data suggest that (a) security analyst teams, when conducting collaborative correlation analysis, could be inefficient in pooling unique information from their peers; (b) employing off-the-shelf collaboration tools in cybersecurity defense environments is inadequate; and (c) collaborative security visualization tools developed considering the human cognitive limitations of security analysts is necessary. Application: Potential applications of this research include development of team training procedures and collaboration tool development for security analysts.