Advertisement

PRIDE: Practical Intrusion Detection in Resource Constrained Wireless Mesh Networks

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8233)

Abstract

As interest in wireless mesh networks grows, security challenges, e.g., intrusion detection, become of paramount importance. Traditional solutions for intrusion detection assign full IDS responsibilities to a few selected nodes. Recent results, however, have shown that a mesh router cannot reliably perform full IDS functions because of limited resources (i.e., processing power and memory). Cooperative IDS solutions, targeting resource constrained wireless networks impose high communication overhead and detection latency. To address these challenges, we propose PRIDE (PRactical Intrusion DEtection in resource constrained wireless mesh networks), a non-cooperative real-time intrusion detection scheme that optimally distributes IDS functions to nodes along traffic paths, such that detection rate is maximized, while resource consumption is below a given threshold. We formulate the optimal IDS function distribution as an integer linear program and propose algorithms for solving it accurately and fast (i.e., practical). We evaluate the performance of our proposed solution in a real-world, department-wide, mesh network.

Keywords

wireless mesh network intrusion detection resource constraints integer linear programming real-world implementation 

References

  1. 1.
    Hiertz, G.R., Denteneer, D., Max, S., Taori, R., Cardona, J., Berlemann, L., Walke, B.: IEEE 802.11s: the WLAN mesh standard. Wireless Commun. (2010)Google Scholar
  2. 2.
    Amir, Y., Danilov, C., Musăloiu-Elefteri, R., Rivera, N.: The SMesh wireless mesh network. ACM Transactions on Computer Systems (September 2008)Google Scholar
  3. 3.
    Backens, J., Mweemba, G., van Stam, G.: A rural implementation of a 52 node mixed wireless mesh network in macha, zambia. In: Villafiorita, A., Saint-Paul, R., Zorer, A. (eds.) AFRICOM 2009. LNICST, vol. 38, pp. 32–39. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  4. 4.
    Chenji, H., Hassanzadeh, A., Won, M., Li, Y., Zhang, W., Yang, X., Stoleru, R., Zhou, G.: A wireless sensor, adhoc and delay tolerant network system for disaster response. LENSS-09-02, Tech. Rep. (2011)Google Scholar
  5. 5.
    Hassanzadeh, A., Stoleru, R., Shihada, B.: Energy efficient monitoring for intrusion detection in battery-powered wireless mesh networks. In: ADHOC-NOW (2011)Google Scholar
  6. 6.
    Shin, D.-H., Bagchi, S., Wang, C.-C.: Distributed online channel assignment toward optimal monitoring in multi-channel wireless networks. In: IEEE INFOCOM (2012)Google Scholar
  7. 7.
    Hugelshofer, F., Smith, P., Hutchison, D., Race, N.J.: OpenLIDS: a lightweight intrusion detection system for wireless mesh networks. In: MobiCom (2009)Google Scholar
  8. 8.
    Hassanzadeh, A., Stoleru, R.: Towards optimal monitoring in cooperative ids for resource constrained wireless networks. In: IEEE ICCCN (2011)Google Scholar
  9. 9.
    Krontiris, I., Benenson, Z., Giannetsos, T., Freiling, F.C., Dimitriou, T.: Cooperative intrusion detection in wireless sensor networks. In: Roedig, U., Sreenan, C.J. (eds.) EWSN 2009. LNCS, vol. 5432, pp. 263–278. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  10. 10.
    Hassanzadeh, A., Stoleru, R.: On the optimality of cooperative intrusion detection for resource constrained wireless networks. Computers & Security (2013)Google Scholar
  11. 11.
    Sekar, V., Krishnaswamy, R., Gupta, A., Reiter, M.K.: Network-wide deployment of intrusion detection and prevention systems. In: ACM CoNEXT (2010)Google Scholar
  12. 12.
    Hassanzadeh, A., Xu, Z., Stoleru, R., Gu, G.: Practical intrusion detection in resource constrained wireless mesh networks. Texas A&M University 2012-7-1, Tech. Rep. (2012)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringTexas A&M UniversityUSA
  2. 2.Computer Science DepartmentColumbia UniversityUSA

Personalised recommendations