Skip to main content
SpringerLink
Log in

Locating Malicious Agents in Mobile Wireless Sensor Networks

  • Conference paper
PRIMA 2014: Principles and Practice of Multi-Agent Systems (PRIMA 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8861))

  • 1244 Accesses

Abstract

A compromised node in wireless sensor networks can be used to create false messages by generating them on their own or by fabricating legitimate messages received from other nodes. Our goal is to locate the compromised nodes that create false messages. Existing studies can only be used in situations where sensor nodes do not move. However, it is possible that nodes move because of wind or other factors in real situations. We improve existing studies for detecting compromised nodes in mobile wireless sensor networks. In the proposed method, an agent exists on each node and it appends its ID and a k-bit code to an event message and the sink detects a compromised node by a statistical method. Our method can be used in static and dynamic environments. Simulations we conducted prove the effectiveness of our method.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Cao, Z., Deng, H., Guan, Z., Chen, Z.: Information-theoretic modeling of false data filtering schemes in wireless sensor networks. ACM Trans. Sensor Networks 8(2), 1–19 (2012)

    Article  Google Scholar 

  2. Chen, M., Kwon, T., Yuan, Y., Leung, V.C.: Mobile agent based wireless sensor networks. Journal of Computers 1(1), 14–21 (2006)

    Article  Google Scholar 

  3. Dini, G., Lo Duca, A.: Towards a reputation-based routing protocol to contrast blackholes in a delay tolerant network. Ad Hoc Networks 10(7), 1167–1178 (2012)

    Article  Google Scholar 

  4. Dong, Q., Banerjee, S., Adler, M., Hirata, K.: Efficient probabilistic packet marking. In: Proc. IEEE ICNP, pp. 368–377 (2005)

    Google Scholar 

  5. Ganesan, P., Venugopalan, R., Peddabachagari, P., Dean, A., Mueller, F., Sichitiu, M.: Analyzing and modeling encryption overhead for sensor network nodes. In: Proc. ACM WSNA, pp. 151–159 (2003)

    Google Scholar 

  6. Gezer, C., Niccolini, M., Buratti, C.: An IEEE 802.15.4/ZigBee based wireless sensor network for Energy Efficient Buildings. In: Proc. IEEE WiMob., pp. 486–491. IEEE (2010)

    Google Scholar 

  7. Hansen, M.T.: Asynchronous group key distribution on top of the cc2420 security mechanisms for sensor networks. In: Proc. ACM WiSec, pp. 13–20 (2009)

    Google Scholar 

  8. Jin, X., Putthapipat, P., Pan, D., Pissinou, N., Makki, S.K.: Unpredictable Software-based Attestation Solution for node compromise detection in mobile WSN. In: 2010 IEEE Globecom Workshops, pp. 2059–2064 (2010)

    Google Scholar 

  9. Karlof, C., Wagner, D.: Secure routing in wireless sensor networks: Attacks and countermeasures. In: IEEE SNPA, pp. 113–127 (2003)

    Google Scholar 

  10. Karp, B., Kung, H.T.: GPSR: Greedy perimeter stateless routing for wireless networks. In: Proc. ACM MOBICOM, pp. 243–254 (2000)

    Google Scholar 

  11. Khalil, I., Bagchi, S., Nina-Rotaru, C.: Dicas: Detection, diagnosis and isolation of control attacks in sensor networks. In: SecureComm, pp. 89–100 (2005)

    Google Scholar 

  12. Khalil, I., Bagchi, S., Shroff, N.B.: Liteworp: Detection and isolation of the wormhole attack in static multihop wireless networks. Comput. Netw. 51(13), 3750–3772 (2007)

    Article  MATH  Google Scholar 

  13. Krawczyk, H., Bellare, M., Canetti, R.: HMAC: Keyed-hashing for message authentication. In: iETF - Network Working Group (February 1997), RFC2104

    Google Scholar 

  14. Li, F., Wu, J.: A probabilistic voting-based filtering scheme in wireless sensor networks. In: ACM IWCMC, pp. 27–32 (2006)

    Google Scholar 

  15. Liu, B., Dousse, O., Nain, P., Towsley, D.: Dynamic Coverage of Mobile Sensor Networks. IEEE Trans. Parallel and Distributed Systems 24(2), 301–311 (2013)

    Article  Google Scholar 

  16. Lu, R., Member, S., Lin, X., Zhu, H.: BECAN: A Bandwidth-Efficient Cooperative Authentication Scheme for Filtering Injected False Data in Wireless Sensor Networks. IEEE Trans. Parallel Distrib. Syst. 23(1), 32–43 (2012)

    Article  Google Scholar 

  17. Marti, S., Giuli, T.J., Lai, K., Baker, M.: Mitigating routing misbehavior in mobile ad hoc networks. In: Proc. ACM MOBICOM, pp. 255–265 (2000)

    Google Scholar 

  18. Platon, E., Sei, Y.: Security software engineering in wireless sensor networks. Progress in Informatics 5(1), 49–64 (2008)

    Article  Google Scholar 

  19. Ramadan, R.A.: Agent Based Multipath Routing in wireless sensor networks. In: IEEE Symposium on Intelligent Agents, pp. 63–69 (2009)

    Google Scholar 

  20. Sei, Y., Ohsuga, A.: Need Only One Bit: Light-weight Packet Marking for Detecting Compromised Nodes in WSNs. In: Proc. 7th SECURWARE, pp. 134–143 (2013)

    Google Scholar 

  21. Seshadri, A., Perrig, A., van Doorn, L., Khosla, P.: SWATT: Software-based attestation for embedded devices. In: Proc. IEEE S&P, pp. 272–282 (2004)

    Google Scholar 

  22. Song, D.X., Perrig, A.: Advanced and authenticated marking schemes for IP traceback. In: IEEE INFOCOM, pp. 878–886 (2001)

    Google Scholar 

  23. Wang, G., Zhang, W., Cao, G., Porta, T.: On supporting distributed collaboration in sensor networks. In: Proc. IEEE MILCOM, pp. 752–757 (2003)

    Google Scholar 

  24. Wood, A.D., Stankovic, J.A.: Denial of service in sensor networks. Trans. IEEE Computer 35(10), 54–62 (2002)

    Google Scholar 

  25. Xu, E., Ding, Z., Dasgupta, S.: Target Tracking and Mobile Sensor Navigation in Wireless Sensor Networks. IEEE Trans. Mobile Computing 12(1), 177–186 (2013)

    Article  Google Scholar 

  26. Xu, Z., Hsu, H., Chen, X., Zhu, S., Hurson, A.R.: AK-PPM: An authenticated packet attribution scheme for mobile ad hoc networks. In: Balzarotti, D., Stolfo, S.J., Cova, M. (eds.) RAID 2012. LNCS, vol. 7462, pp. 147–168. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  27. Yang, H., Ye, F., Yuan, Y., Lu, S., Arbaugh, W.: Toward resilient security in wireless sensor networks. In: ACM MOBIHOC, pp. 34–45 (2005)

    Google Scholar 

  28. Yang, Y., Wang, X., Zhu, S., Cao, G.: Distributed software-based attestation for node compromise detection in sensor networks. In: Proc. IEEE SRDS, pp. 219–230 (2007)

    Google Scholar 

  29. Ye, F., Luo, H., Lu, S., Zhang, L.: Statistical en-route filtering of injected false data in sensor networks. IEEE Journal on Selected Areas in Communications 23(4), 839–850 (2005)

    Article  Google Scholar 

  30. Ye, F., Yang, H., Liu, Z.: Catching “Moles” in Sensor Networks. In: Proc. IEEE ICDCS, p. 69 (2007)

    Google Scholar 

  31. Ye, F., Zhong, G., Lu, S., Zhang, L.: Gradient broadcast: a robust data delivery protocol for large scale sensor networks. Wirel. Netw. 11(3), 285–298 (2005)

    Article  Google Scholar 

  32. Yu, Z., Guan, Y.: A dynamic en-route scheme for filtering false data injection in wirelesssensor networks. In: Proc. IEEE INFOCOM, pp. 1–12 (2006)

    Google Scholar 

  33. Zhang, Q., Zhou, X., Yang, F., Li, X.: Contact-based traceback in wireless sensor networks. In: Proc. IEEE WiCom, pp. 2487–2490 (2007)

    Google Scholar 

  34. Zhu, S., Setia, S., Jajodia, S., Ning, P.: An interleaved hop-by-hop authentication scheme for filtering of injected false data in sensor networks. In: IEEE S&P, pp. 259–271 (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Graduate School of Information Systems, The University of Electro-Communications, Tokyo, Japan

    Yuichi Sei & Akihiko Ohsuga

Authors
  1. Yuichi Sei
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Akihiko Ohsuga
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Computer Science and Software Engineering, University of Wollongong, Northfields Avenue, 2522, Wollongong, NSW, Australia

    Hoa Khanh Dam

  2. Imperial College, SW7 2BT, London, UK

    Jeremy Pitt

  3. University of Electronic Science and Technology of China, 610051, Chengdu, Sichuan, China

    Yang Xu

  4. NICTA Queensland Research Laboratory, GPO Box 2434, 4001, Brisbane, QLD, Australia

    Guido Governatori

  5. Nagoya Institute of Technology, Gokiso-cho, 466-8555, Showa-ku, Nagoya, Japan

    Takayuki Ito

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Sei, Y., Ohsuga, A. (2014). Locating Malicious Agents in Mobile Wireless Sensor Networks. In: Dam, H.K., Pitt, J., Xu, Y., Governatori, G., Ito, T. (eds) PRIMA 2014: Principles and Practice of Multi-Agent Systems. PRIMA 2014. Lecture Notes in Computer Science(), vol 8861. Springer, Cham. https://doi.org/10.1007/978-3-319-13191-7_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-13191-7_17

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13190-0

  • Online ISBN: 978-3-319-13191-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation