Network security

Larson, Nathan (2011): Network security.

Abstract

In a variety of settings, some payoff-relevant item spreads along a network of connected individuals. In some cases, the item will benefit those who receive it (for example, a music download, a stock tip, news about a new research funding source, etc.) while in other cases the impact may be negative (for example, viruses, both biological and electronic, financial contagion, and so on). Often, good and bad items may propagate along the same networks, so individuals must weigh the costs and benefits of being more or less connected to the network. The situation becomes more complicated (and more interesting) if individuals can also put effort into security, where security can be thought of as a screening technology that allows an individual to keep getting the benefits of network connectivity while blocking out the bad items. Drawing on the network literatures in economics, epidemiology, and applied math, we formulate a model of network security that can be used to study individual incentives to expand and secure networks and characterize properties of a symmetric equilibrium.

• Item Type: MPRA Paper
• Language: English
• Keywords: social networks; network security; network robustness; contagion; random graphs
• Subjects: I - Health, Education, and Welfare > I1 - Health > I18 - Government Policy ; Regulation ; Public Health; D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D85 - Network Formation and Analysis: Theory; C - Mathematical and Quantitative Methods > C7 - Game Theory and Bargaining Theory > C73 - Stochastic and Dynamic Games ; Evolutionary Games ; Repeated Games

References

[1] Anderson, Ross, and Tyler Moore (2006), “The Economics of Information Security,” Science 314, 610.

[2] Azaiez, M. and V. Bier, “Optimal Resource Allocation for Security in Reliability Systems,” working paper.

[3] Bala, Venkatesh, and Sanjeev Goyal (2000), “A Noncooperative Model of Network Formation,” Econometrica, 68(5), 1181-1229.

[4] Chung, F. and L. Lu (2002), “Connected Components in Random Graphs with Given Degree Sequences,” Annals of Combinatorics, 6, 125-145.

[5] Durrett, Rick (2007), Random Graph Dynamics, Cambridge University Press.

[6] Goyal, Sanjeev (2007), Connections: An Introduction to the Economics of Networks, Princeton University Press.

[7] Goyal, Sanjeev and Adrien Vigier, “Robust Networks,” working paper, 2011.

[8] Hong, Songhoon (2008), “Hacking-proofness and stability in a model of information security networks,” working paper.

[9] Hoyer, Britta and Kris De Jaegher, “Strategic Network Disruption and Defense,” working paper.

[10] Jackson, Matthew (2008), Social and Economic Networks, Princeton University Press.

[11] Jackson, Matthew and Asher Wolinsky (1996), “A Strategic Model of Social and Economic Networks,” Journal of Economic Theory, 71(1), 44-74.

[12] Kovenock, Dan and Brian Roberson (2010), “The Optimal Defense of Networks of Targets,” Purdue University Economics Working Papers 1251.

[13] Molloy, M. and B. Reed (1998), “The Size of the Largest Component of a Random Graph on a Fixed Degree Sequence,” Combinatorics, Probability and Computing, 7, 295-306.

[14] Molloy, M. and B. Reed (1995), “A Critical Point for Random Graphs with a Given Degree Sequence,” Random Structures and Algorithms, 6, 161-180.

[15] Newman, Mark (2002), “The spread of epidemic disease on networks,” Phys. Rev. E 66, 016128.

[16] Newman, M., S. Strogatz, and D. Watts (2001), “Random Graphs with Arbitrary Degree Distributions And Their Applications,” Phys. Rev. E 64, 026118.

[17] Vega-Redondo (2007), Complex Social Networks, Cambridge University Press. 32