TY - GEN
T1 - Uncertainty in interdependent security games
AU - Johnson, Benjamin
AU - Grossklags, Jens
AU - Christin, Nicolas
AU - Chuang, John
N1 - Funding Information:
This research was supported in part by CyLab at Carnegie Mellon under grant DAAD19-02-1-0389 from the Army Research Office, and by the National Science Foundation through award CCF-0424422 (TRUST - Team for Research in Ubiquitous Secure Technology).
PY - 2010
Y1 - 2010
N2 - Even the most well-motivated models of information security have application limitations due to the inherent uncertainties involving risk. This paper exemplifies a formal mechanism for resolving this kind of uncertainty in interdependent security (IDS) scenarios. We focus on a single IDS model involving a computer network, and adapt the model to capture a notion that players have only a very rough idea of security threats and underlying structural ramifications. We formally resolve uncertainty by means of a probability distribution on risk parameters that is common knowledge to all players. To illustrate how this approach might yield fruitful applications, we postulate a well-motivated distribution, compute Bayesian Nash equilibria and tipping conditions for the derived model, and compare these with the analogous conditions for the original IDS model.
AB - Even the most well-motivated models of information security have application limitations due to the inherent uncertainties involving risk. This paper exemplifies a formal mechanism for resolving this kind of uncertainty in interdependent security (IDS) scenarios. We focus on a single IDS model involving a computer network, and adapt the model to capture a notion that players have only a very rough idea of security threats and underlying structural ramifications. We formally resolve uncertainty by means of a probability distribution on risk parameters that is common knowledge to all players. To illustrate how this approach might yield fruitful applications, we postulate a well-motivated distribution, compute Bayesian Nash equilibria and tipping conditions for the derived model, and compare these with the analogous conditions for the original IDS model.
UR - http://www.scopus.com/inward/record.url?scp=78650721633&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-17197-0_16
DO - 10.1007/978-3-642-17197-0_16
M3 - Conference contribution
AN - SCOPUS:78650721633
SN - 3642171966
SN - 9783642171963
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 234
EP - 244
BT - Decision and Game Theory for Security - First International Conference, GameSec 2010, Proceedings
T2 - 1st International Conference on Decision and Game Theory for Security, GameSec 2010
Y2 - 22 November 2010 through 23 November 2010
ER -