# Threat Assessment Of A Possible Vehicle-Born Improvised Explosive Device Using Dsmt

Jean Dezert French Aerospace Lab.

ONERA/DTIM/SIF
29 Av. de la Div. Leclerc 92320 Chˆatillon, France.

jean.dezert@onera.fr Abstract - **This paper presents the solution about the** threat of a VBIED (Vehicle-Born Improvised Explosive Device) obtained with the DSmT (Dezert-Smarandache Theory). This problem has been proposed recently to the authors by Simon Maskell and John Lavery as a typical illustrative example to try to compare the different approaches for dealing with uncertainty for decisionmaking support. The purpose of this paper is to show in details how a solid justified solution can be obtained from DSmT approach and its fusion rules thanks to a proper modeling of the belief functions involved in this problem.

Keywords: **Security, Decison-making support, Information fusion, DSmT, Threat assessment.**

## 1 The Vbied Problem

- Concern**: VBIED (Vehicle-Born Improvised Explosive Device) attack on an administrative building** B
- Prior information**: We consider an Individual**
A **under surveillance due to previous unstable behavior who drives customized white Toyota (WT)**
vehicle.

- Observation done at time t − **10 min: From a**
video sensor on road that leads to building B 10 min ago, one has observed a White Toyota 200m from the building B **traveling in normal traffic flow**
toward building B**. We consider the following two**
sources of information based on this video observation available at time t − **10 min:**
Page 1
- Source 1**: An Analyst 1 with 10 years experience analyses the video and concludes that**
individual A **is now probably near building** B.

- Source 2**: An Automatic Number Plate**
Recognition (ANPR) system analyzing same video outputs 30% probability that the vehicle is individual A**'s white Toyota.**
Florentin Smarandache ENSIETA
E
3I
2-EA3876 Laboratory 2 rue Fran¸cois Verny 29806 Brest Cedex 9, France.

Florentin.Smarandache@ensieta.fr
- Observation done at time t − **5 min: From a**
video sensor on road 15km from building B **5 min**
ago one gets a video that indicates a white Toyota with some resemblance to individual A**'s white**
Toyota. We consider the following thrid source of information based on this video observation available at time t − **5 min:**
- Source 3: An Analyst 2 (new in post) analyses this video and concludes that it is improbable that individual A **is near building** B.

- Question 1**: Should building B be evacuated?**
- Question 2**: Is experience (Analyst 1) more valuable than physics (the ANPR system) combined**
with inexperience (Analyst 2)? How do we model that?

NOTE: Deception (e.g., individual A **using different**
car, false number plates, etc.) and biasing (on the part of the analysts) are often a part of reality, but they are not part of this example.

## 2 Modeling The Vbied Problem

Before applying DSmT fusion techniques to solve this VBIED problem it is important to model the problem in the framework of belief functions.

## 2.1 Marginal Frames With Their Models

The marginal frames involved in this problem are: - **Frame related with individuals:**
Θ1 = {A = Suspicious person, A¯ **= not** A}
- **Frame related with the vehicle:**