ACM Home Page
Please provide us with feedback. Feedback
A local mean field analysis of security investments in networks
Full text PdfPdf (188 KB)
Source
Applications, Technologies, Architectures, and Protocols for Computer Communication archive
Proceedings of the 3rd international workshop on Economics of networked systems table of contents
Seattle, WA, USA
SESSION: Session 2 table of contents
Pages 25-30  
Year of Publication: 2008
ISBN:978-1-60558-179-8
Authors
Marc Lelarge  INRIA-ENS, Paris, France
Jean Bolot  SPRINT, Burlingame, USA
Sponsors
ACM: Association for Computing Machinery
SIGCOMM: ACM Special Interest Group on Data Communication
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 3,   Downloads (12 Months): 66,   Citation Count: 1
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1403027.1403034
What is a DOI?

ABSTRACT

Getting agents in the Internet, and in networks in general, to invest in and deploy security features and protocols is a challenge, in particular because of economic reasons arising from the presence of network externalities. Our goal in this paper is to model and investigate the impact of such externalities on security investments in a network.

Specifically, we study a network of interconnected agents subject to epidemic risks such as viruses and worms where agents can decide whether or not to invest some amount to deploy security solutions. We consider both cases when the security solutions are strong (they perfectly protect the agents deploying them) and when they are weak. We make three contributions in the paper. First, we introduce a general model which combines an epidemic propagation model with an economic model for agents which captures network effects and externalities. Second, borrowing ideas and techniques used in statistical physics, we introduce a Local Mean Field (LMF) model, which extends the standard mean-field approximation to take into account the correlation structure on local neighborhoods. Third, we solve the LMF model in a network with externalities, and we derive analytic solutions for sparse random graphs of agents, for which we obtain asymptotic results. We find known phenomena such as free riders and tipping points. We also observe counter-intuitive phenomena, such as increasing the quality of the security technology can result in a decreased adoption of that technology in the network. In general, we find that both situations with strong and weak protection exhibit externalities and that the equilibrium is not socially optimal - therefore there is a market failure. Insurance is one mechanism to address this market failure. In related work, we have shown that insurance is a very effective mechanism [3,4], and argue that using insurance would increase the security in a network such as the Internet.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
D. Aldous and A. Bandyopadhyay. A survey of max-type recursive distributional equations. The Annals of Applied Probability, vol. 15, pp. 1047--1110, 2005.
 
2
D. Aldous and J. M. Steeele. The objective method: probabilistic combinatorial optimization and local weak convergence. Probability on discrete structures, Springer, vol. 110, pp. 1--72, 2004.
 
3
J. Bolot and M. Lelarge. A New Perspective on Internet Security using Insurance. Proc. IEEE Infocom 2008.
 
4
J. Bolot and M. Lelarge. Cyber-insurance as an incentive for IT security. Proc. Workshop Economics of Information Security (WEIS), 2008.
 
5
E. G. Coffman Jr., Z. Ge, V. Misra. Network resilience: exploring cascading failures within BGP. Proc. 40th Annual Allerton Conference on Communications, Computing and Control, October 2002.
 
6
 
7
A. Ganesh, L. Massoulie, D. Towsley. The effect of network topology on the spread of epidemics. Proc. IEEE Infocom 2005, Miami, FL, March 2005.
 
8
C. Gollier. The Economics of Risk and Time. MIT Press, 2004.
 
9
H. Kunreuther and G. Heal. Interdependent security: the case of identical agents. Journal of Risk and Uncertainty, 26(2):231--249, 2003.
10
 
11
M. Lelarge and J. Bolot. A Local Mean Field Analysis of Security Investments in Networks. arXiv:0803.3455, 2008.
12
 
13
N. Nisan, T. Roughgarden, E. Tardos and V. V. Vazirani (eds). Algorithmic game theory. Cambridge University Press, 2007.
14
 
15
White House. "National Strategy to Secure Cyberspace", 2003. Available at whitehouse.gov/pcipb.
16


Collaborative Colleagues:
Marc Lelarge: colleagues
Jean Bolot: colleagues