intentionalattacks {bnRep}R Documentation

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.


[Package bnRep version 0.0.1 Index]