Page 121 - KDU INTERNATIONAL JOURNAL OF CRIMINAL JUSTICE

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

analyzing variables such as his access privileges, communication patterns, and
job role, a Bayesian network could have identified deviations from normal

behavior and triggered alerts for further investigation.

While specific case studies that combine insider threat and espionage mapping

with Bayesian theorem may be limited, there are several examples of real-world
scenarios where Bayesian reasoning and probabilistic modeling have been
applied to detect and analyze insider threats and espionage activities. These case

studies demonstrate the potential effectiveness of Bayesian theorem in
enhancing threat detection capabilities. Here are a few notable examples:

2. Chelsea Manning and the WikiLeaks Incident

Chelsea Manning, a former U.S. Army intelligence analyst, leaked classified
documents to WikiLeaks in 2010. Bayesian reasoning can be applied to model

and analyze Manning's behaviors leading up to the incident, such as accessing
sensitive files, data exfiltration patterns, and changes in communication
patterns. By incorporating Bayesian networks, security analysts can update the

probabilities of different variables based on observed behaviors, allowing for
more accurate identification and prediction of insider threats.

3. The Stuxnet Attack on Iranian Nuclear Facilities

The Stuxnet worm, which targeted Iran's nuclear program, involved a
combination of cyber espionage and insider involvement. Bayesian modeling

can be used to analyze various data sources, including network traffic data,
system logs, and behavioral patterns of employees involved in the incident. By
leveraging Bayesian networks, security analysts can integrate these sources of

evidence, update probabilities, and identify patterns that may indicate both
insider involvement and the presence of espionage activities.

4. Chinese Espionage and Advanced Persistent Threats (APTs)

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