Why Cybersecurity Needs Probability — Not Predictions

Summary: This commentary emphasizes the importance of understanding probabilities over predictions in the cybersecurity landscape. It advocates for Bayesian probability models to assess risks and improve resilience against cyber threats. By leveraging insurance data and advanced risk assessments, organizations can enhance their security strategies and better withstand cyberattacks.

Affected: Cybersecurity companies and organizations impacted by cyber threats

Keypoints :

• Predictions in cybersecurity are often impractical; a better understanding of probabilities can inspire effective solutions.
• Bayesian probability allows for risk modeling that adapts to dynamic cybersecurity threats.
• Organizations are becoming more resilient, evidenced by a decrease in the material impact of cyberattacks despite a rise in claim frequency.
• Data-driven probability models enable informed decisions about potential cyber threats and associated losses.
• Assuming FUD can cloud judgment in cybersecurity; focusing on data improves risk assessment and strengthens organizational defenses.