TY - GEN
T1 - Secure or insure? a game-theoretic analysis of information security games
AU - Grossklags, Jens
AU - Christin, Nicolas
AU - Chuang, John
PY - 2008
Y1 - 2008
N2 - Despite general awareness of the importance of keeping one's system secure, and widespread availability of consumer security technologies, actual investment in security remains highly variable across the Internet population, allowing attacks such as distributed denial-of-service (DDoS) and spam distribution to continue unabated. By modeling security investment decision-making in established (e.g., weakest-link, best-shot) and novel games (e.g., weakest-target), and allowing expenditures in self-protection versus self-insurance technologies, we can examine how incentives may shift between investment in a public good (protection) and a private good (insurance), subject to factors such as network size, type of attack, loss probability, loss magnitude, and cost of technology. We can also characterize Nash equilibria and social optima for different classes of attacks and defenses. In the weakest-target game, an interesting result is that, for almost all parameter settings, more effort is exerted at Nash equilibrium than at the social optimum. We may attribute this to the "strategic uncertainty" of players seeking to self-protect at just slightly above the lowest protection level.
AB - Despite general awareness of the importance of keeping one's system secure, and widespread availability of consumer security technologies, actual investment in security remains highly variable across the Internet population, allowing attacks such as distributed denial-of-service (DDoS) and spam distribution to continue unabated. By modeling security investment decision-making in established (e.g., weakest-link, best-shot) and novel games (e.g., weakest-target), and allowing expenditures in self-protection versus self-insurance technologies, we can examine how incentives may shift between investment in a public good (protection) and a private good (insurance), subject to factors such as network size, type of attack, loss probability, loss magnitude, and cost of technology. We can also characterize Nash equilibria and social optima for different classes of attacks and defenses. In the weakest-target game, an interesting result is that, for almost all parameter settings, more effort is exerted at Nash equilibrium than at the social optimum. We may attribute this to the "strategic uncertainty" of players seeking to self-protect at just slightly above the lowest protection level.
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U2 - 10.1145/1367497.1367526
DO - 10.1145/1367497.1367526
M3 - Conference contribution
AN - SCOPUS:57349198694
SN - 9781605580852
T3 - Proceeding of the 17th International Conference on World Wide Web 2008, WWW'08
SP - 209
EP - 218
BT - Proceeding of the 17th International Conference on World Wide Web 2008, WWW'08
PB - Association for Computing Machinery
T2 - 17th International Conference on World Wide Web 2008, WWW'08
Y2 - 21 April 2008 through 25 April 2008
ER -