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Understanding Cyber Situational Awareness in a Cyber Security Game involving Recommendations

Author

Listed:
  • Palvi Aggarwal

    (IIT Mandi - Indian Institute of Technology Mandi, CMU - Carnegie Mellon University [Pittsburgh])

  • Frederic Moisan

    (CMU - Carnegie Mellon University [Pittsburgh])

  • Cleotilde Gonzalez

    (CMU - Carnegie Mellon University [Pittsburgh])

  • Varun Dutt

    (IIT Mandi - Indian Institute of Technology Mandi)

Abstract

Intrusion Detection Systems (IDSs) help in creating cyber situational awareness for defenders by providing recommendations. Prior research in simulation and game-theory has revealed that the presence and accuracy of IDS-like recommendations influence the decisions of defenders and adversaries. In the current paper, we present novel analyses of prior research by analyzing the sequential decisions of defenders and adversaries over repeated trials. Specifically, we developed computational cognitive models based upon Instance-Based Learning Theory (IBLT) to capture the dynamics of the sequential decisions made by defenders and adversaries across numerous conditions that differed in the IDS's availability and accuracy. We found that cognitive mechanisms based upon recency, frequency, and variability helped account for adversarial and defender decisions better than the optimal Nash solutions. We discuss the implications of our results for adversarial-and-defender decisions in the cyber-world.

Suggested Citation

  • Palvi Aggarwal & Frederic Moisan & Cleotilde Gonzalez & Varun Dutt, 2018. "Understanding Cyber Situational Awareness in a Cyber Security Game involving Recommendations," Post-Print hal-03188216, HAL.
    • Handle: RePEc:hal:journl:hal-03188216
    DOI: 10.22619/IJCSA.2018.100118
    Note: View the original document on HAL open archive server: https://hal.science/hal-03188216
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