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Dynamic Bayesian Networks, Elicitation, and Data Embedding for Secure Environments.

Kieran Drury¹, Jim Q Smith¹

¹Department of Statistics, University of Warwick, Coventry CV4 7AL, UK.

Entropy (Basel, Switzerland)

|November 27, 2024

Summary

This study introduces a secure protocol for serious crime modeling, enabling police to use academic models with confidential data for real-time decision support. It addresses data scarcity by matching ongoing incidents to a library of criminal plot models.

Keywords:

Bayesian networks causality crime intervention decision support systems dynamic Bayesian networks elicitation expert judgement missing data model libraries

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Area of Science:

Computational criminology
Artificial intelligence in law enforcement
Formal methods for security

Background:

Serious crime modeling requires secure environments, limiting academic access to police data.
Real-time decision-making is hindered by sparse and confidential data available to law enforcement.
Existing models often cannot incorporate sensitive, real-time police intelligence.

Purpose of the Study:

To develop a formal protocol for securely translating academic crime models for police use.
To enable the creation of model libraries for real-time criminal plot recognition.
To address challenges of data missingness in secure, sensitive environments.

Main Methods:

Development of a formal protocol using graphical models for secure translation.
Creation of a framework for building and utilizing libraries of criminal plot models.
Illustrative embedding of a vehicle attack scenario into the police model library.

Main Results:

A secure protocol was developed for translating academic base models to police-embellished models.
The first demonstration of building and using model libraries for real-time decision support in secure environments.
Successful illustration of integrating new criminal plot types (e.g., vehicle attacks) into the library.

Conclusions:

The protocol ensures sensitive police data remains secure while enabling formal integration of open-source data.
Model libraries facilitate real-time decision support by matching ongoing incidents to known patterns.
This approach enhances police capabilities in addressing serious crime through secure, data-driven modeling.