intentionalattacks: intentionalattacks Bayesian Network

In bnRep: A Repository of Bayesian Networks from the Academic Literature

intentionalattacks Bayesian Network

Description

Probability elicitation for Bayesian networks to distinguish between intentional attacks and accidental technical failures.

Format

A discrete Bayesian network modeling a floodgate in the Netherlands. Probabilities were given within the referenced paper. The vertices are:

X1

Weak physical access-control (True, False);

X2

Sensor data integrity verification (True, False);

U1

Lack of physical maintenance (True, False);

U2

Well-written maintenance procedure (True, False);

Y

Major cause for sensor sends incorrect water level measurements (Intentional Attack, Accidental Technical Failure);

Z1

Abnormalities in the other locations (True, False);

Z2

Sensor sends correct water level measurements after cleaning the sensor (True, False)

Z3

Sensor sends correct water level measurements after recalibrating the sensor (True, False);

Value

An object of class bn.fit. Refer to the documentation of bnlearn for details.

References

Chockalingam, S., Pieters, W., Teixeira, A. M., & van Gelder, P. (2023). Probability elicitation for Bayesian networks to distinguish between intentional attacks and accidental technical failures. Journal of Information Security and Applications, 75, 103497.

bnRep documentation built on April 12, 2025, 1:13 a.m.