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Information-Pooling Bias in Collaborative Security Incident Correlation Analysis
Prashanth Rajivan1, Nancy J Cooke1
1Arizona State University, Mesa.
Human Factors
|April 4, 2018
Summary
Security teams struggle to share unique information during incident correlation due to information-pooling bias. Specialized visualization tools are needed to improve collaborative threat detection and overcome cognitive limitations.
Area of Science:
- Cybersecurity
- Human-Computer Interaction
- Cognitive Psychology
Background:
- Information-pooling bias hinders teams from sharing unique data.
- This bias's impact on cybersecurity team collaboration is understudied.
Purpose of the Study:
- To investigate the effect of group-level information-pooling bias on collaborative incident correlation.
- To evaluate the efficacy of different collaboration aids in mitigating this bias.
Main Methods:
- Thirty 3-person teams performed threat detection and incident correlation tasks.
- Teams used varying collaboration aids under a hidden profile paradigm.
- Communication patterns were analyzed to assess information sharing.
Main Results:
- Teams predominantly discussed commonly known information, neglecting unique data.
- Unaided collaboration proved inefficient for correlating unique security incidents.
- Visualizations effectively mitigated information-pooling bias by enhancing perception and memory.
Conclusions:
- Security analyst teams may be inefficient at pooling unique information.
- Standard collaboration tools are insufficient for cybersecurity defense.
- Developing collaborative security visualization tools tailored to cognitive limitations is crucial.
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