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Worm Versus Alert: Who Wins in a Battle for Control of a Large-Scale Network?

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Principles of Distributed Systems (OPODIS 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4878))

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Abstract

Consider the following game between a worm and an alert over a network of n nodes. Initially, no nodes are infected or alerted and each node in the network is a special detector node independently with small but constant probability. The game starts with a single node becoming infected. In every round thereafter, every infected node sends out a constant number of worms to other nodes in the population, and every alerted node sends out a constant number of alerts. Nodes in the network change state according to the following four rules: 1) If a worm is received by a node that is not a detector and is not alerted, that node becomes infected; 2) If a worm is received by a node that is a detector, that node becomes alerted; 3) If an alert is received by a node that is not infected, that node becomes alerted; 4) If a worm or an alert is received by a node that is already infected or already alerted, then there is no change in the state of that node.

We make two assumptions about this game. First, that an infected node can send worm messages to any other node in the network but, in contrast, an alerted node can send alert messages only through a previously determined, constant degree overlay network. Second, we assume that the infected nodes are intelligent, coordinated and essentially omniscient. In other words, the infected nodes know everything except for which nodes are detectors and the alerted nodes’ random coin flips i.e. they know the topology of the overlay network used by the alerts; which nodes are alerted and which are infected at any time; where alerts and worms are being sent; the overall strategy used by the alerted nodes; etc. The alerted nodes are assumed to know nothing about which other nodes are infected or alerted, where alerts or worms are being sent, or the strategy used by the infected nodes.

Is there a strategy for the alerted nodes that ensures only a vanishingly small fraction of the nodes become infected, no matter what strategy is used by the infected nodes? Surprisingly, the answer is yes. In particular, we prove that a simple strategy achieves this result with probability approaching 1 provided that the overlay network has good node expansion. Specifically, this result holds if d ≥ α and \(\frac{\alpha}{\beta(1-\gamma)} > \frac{2d}{c}\), where α and β represent the rate of the spread of the alert and worm respectively; γ is the probability that a node is a detector node; d is the degree of the overlay network; and c is the node expansion of the overlay network. Next, we give empirical results that suggest that our algorithms for the alert may be useful in current large-scale networks. Finally, we show that if the overlay network has poor expansion, in particular if (1 − γ)β> d, then the worm will likely infect almost all of the non-detector nodes.

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References

  1. Costa, M., Crowcroft, J., Castro, M., Rowstron, A.: Can we contain internet worms? In: Proceedings of the 3rd Workshop on Hot Topics in Networks (HotNets-III) (2004)

    Google Scholar 

  2. Spafford, E.: Exploring Grand Challenges in Trustworthy Computing., http://digitalenterprise.org/seminar/spafford2.html

  3. Moore, D., Paxson, V., Savage, S., Shannon, C., Staniford, S., Weaver, N.: Inside the Slammer Worm. IEEE Security and Privacy journal 1(4), 33–39 (2003)

    Article  Google Scholar 

  4. Davis, A.: Computer Worm Snarls Web (2004), http://www.bayarea.com/mld/mercurynews/5034748.html

  5. Lemos, R.: Slammer Attacks May Become Way of Life for the Net (2003), http://www.news.com/2009-1001-983540.html?tag=fd_lede2_hed

  6. Jr., R.O.: Internet Worm Unearths New Holes (2003), http://www.securityfocus.com/news/2186

  7. Sturgeon, W.: Denial-of-service-attack victim speaks out (2005), http://www.zdnetasia.com/insight/business/0,39044868,39233051,00.htm

  8. Baker, S., Grow, B.: Gambling Sites, This Is A Holdup (2005), http://www.businessweek.com/magazine/content/04_32/b3895106_mz063.htm

  9. Garvey, M.: Phishing Attacks Show Sixfold Increase This Year (2005), http://www.informationweek.com/story/showArticle.jhtml?articleID=164302582

  10. Talbot, C.: Phishing Attacks Up More Than 200% in May, says IBM (2005), http://www.integratedmar.com/ecl-usa/story.cfm?item=19703

  11. Leyden, J.: Phishers Tapping Botnets to Automate Attack (2004), http://www.theregister.co.uk/2004/11/26/anti-phishing_report/

  12. Liet, D.: Most Spam Generated by Botnets, Says Expert (2004), http://news.zdnet.co.uk/internet/security/0,39020375,39167561,00.htm

  13. Leyden, J.: ISPs urged to throttle spam zombies (2005), http://www.theregister.co.uk/2005/05/24/operation_spam_zombie/

  14. Preatoni, R.: Prophet Mohammed protest spreads on the digital ground. In: Hundreds of cyber attacks against Danish and western webservers spreading rage in the name of Allah (2006)

    Google Scholar 

  15. Roberts, P.: Al-Jazeera hobbled by DDOS attack (2003), http://www.infoworld.com/article/03/03/26/HNjazeera_1.html

  16. Costa, M., Crowcroft, J., Castro, M., Rowstron, A., Zhou, L., Zhang, L., Barham, P.: Vigilante: End-to-end containment of internet worms. In: Symposium on Operating System Principles (SOSP) (2005)

    Google Scholar 

  17. Rowstron, A.I.T., Druschel, P.: Pastry: Scalable, decentralized object location, and routing for large-scale peer-to-peer systems. In: Proceedings of the IFIP/ACM International Conference on Distributed Systems Platforms, Heidelberg, pp. 329–350 (2001)

    Google Scholar 

  18. Cooper, C., Dyer, M., Greenhill, C.: Sampling regular graphs and a peer-to-peer network. In: Proceedings of the Sixteenth Annual ACM-SIAM Symposium on Discrete algorithms (SODA) (2005)

    Google Scholar 

  19. Joshi, A., King, S., Dunlap, G., Chen, P.: Detecting past and present intrusions through vulnerability-specific predicates. In: Symposium on Operating System Principles (SOSP) (2005)

    Google Scholar 

  20. Liang, Z., Sekar, R.: Fast and automated generation of attack signatures: a basis for building self-protecting servers. In: Proceedings of the 12th ACM Conference on Computer and Communications Security (CCS), pp. 213–222 (2005)

    Google Scholar 

  21. Brumley, D., Newsome, J., Song, D., Wang, H., Jha, S.: Towards automatic generation of vulnerability-based signatures. In: Proceedings of the IEEE Symposium on Security and Privacy, 2–16 (2006)

    Google Scholar 

  22. Zhou, L., Zhang, L., McSherry, F., Immorlica, N., Costa, M., Chien, S.: A first look at peer-to-peer worms: Threats and defenses. In: Castro, M., van Renesse, R. (eds.) IPTPS 2005. LNCS, vol. 3640, Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  23. Vojnovic, M., Ganesh, A.: On the effectiveness of automatic patching. In: ACM Workshop on Rapid Malcode (WORM) (2005)

    Google Scholar 

  24. Shakkottai, S., Srikant, R.: Peer to peer networks for defense against internet worms. In: Proceedings of the 2006 workshop on Interdisciplinary systems approach in performance evaluation and design of computer and communications sytems (2006)

    Google Scholar 

  25. Bollobas, B.: Random Graphs. Academic Press, London (1985)

    MATH  Google Scholar 

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Eduardo Tovar Philippas Tsigas Hacène Fouchal

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© 2007 Springer-Verlag Berlin Heidelberg

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Aspnes, J., Rustagi, N., Saia, J. (2007). Worm Versus Alert: Who Wins in a Battle for Control of a Large-Scale Network?. In: Tovar, E., Tsigas, P., Fouchal, H. (eds) Principles of Distributed Systems. OPODIS 2007. Lecture Notes in Computer Science, vol 4878. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77096-1_32

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  • DOI: https://doi.org/10.1007/978-3-540-77096-1_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77095-4

  • Online ISBN: 978-3-540-77096-1

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