Page 123 - KDU INTERNATIONAL JOURNAL OF CRIMINAL JUSTICE

KDU International Journal of Criminal Justice (KDUIJCJ)
Volume I | Issue II| July 2024

and historical fraud incidents. By updating probabilities based on observed
anomalies, Bayesian theorem can help identify potential fraud cases, support

forensic investigations, and facilitate proactive fraud prevention measures.

These examples demonstrate the practical application of Bayesian theorem in

behavioral mapping for insider threat and espionage detection. By leveraging
Bayesian networks and the principles of probabilistic reasoning, organizations
can enhance their security posture, identify suspicious patterns, and take

proactive measures to mitigate risks. These real-world cases underscore the
value of Bayesian theorem in analyzing complex relationships and uncertainties

in insider threat and espionage mapping.

Accuracy and Effectiveness

Bayes' theorem plays a critical role in enhancing the accuracy and effectiveness

of behavioral mapping in detecting insider threats and espionage activities. By
incorporating new evidence and updating probabilities, Bayes' theorem
provides a powerful mathematical framework for understanding and identifying

these security risks. Here is an analysis of how Bayes' theorem enhances
accuracy and effectiveness in the context of insider threat and espionage

behavioral mapping.

1. Incorporating New Evidence: One of the key strengths of Bayes' theorem is its

ability to integrate new evidence into the analysis. In the context of insider
threats and espionage, new data points or observations can provide valuable

insights into suspicious behaviors or patterns. By updating the probabilities of
relevant variables based on this new evidence, Bayes' theorem allows for a more

accurate representation of the current threat landscape. This adaptive nature
ensures that the behavioral mapping models remain up-to-date and responsive
to evolving threats.

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