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Intrusion Detection in Homogeneous and Heterogeneous Wireless Sensor Networks


Intrusion detection in Wireless Sensor Network (WSN) is of practical interest in many applications such as detecting an intruder in a battlefield. The intrusion detection is defined as a mechanism for a WSN to detect the existence of inappropriate, incorrect, or anomalous moving attackers. In this paper, we consider this issue according to heterogeneous WSN models. Furthermore, we consider two sensing detection models: single-sensing detection and multiple-sensing detection... Our simulation results show the advantage of multiple sensor heterogeneous WSNs.

Existing System:

  1. In single-sensing detection, At a time  only one intruder detected by the wsn.
  2. Our Previous work was according to homogeneous and heterogeneous single sensor in wireless sensor network

Proposed System:

  1. In Heterogeneous wireless sensor ,Intruder detected anywhere in the network.
  1. We are detecting the intruder in multiple sensor heterogeneous wireless sensor network.


  1. The sensed information provided by a   single sensor might be inadequate for recognizing the intruder.
  2. So that there is no guarantee for our information has been sent securely.

3.  Data will not routed if primary detector fails.


  1. If primary detector fails another detector detect the intruder.
  2. By finding the intruders we can send our information in a secured manner.

System Requirements:


PROCESSOR          :  PENTIUM IV 2.6 GHz
RAM                      :  512 MB DD RAM
MONITOR             :  15” COLOR
HARD DISK            :  20 GB
CDDRIVE              :  LG 52X
                          MOUSE               :  3 BUTTONS


FRONT END                    :  Java
TOOL USED                    :  JFrameBuilder

Bibliography or References

[1] D.P. Agrawal and Q.-A. Zeng, Introduction to Wireless and Mobile Systems. Brooks/Cole Publishing, Aug. 2003.
[2] B. Liu and D. Towsley, “Coverage of Sensor Networks: Fundamental Limits,” Proc. Third IEEE Int’l Conf. Mobile Ad Hoc and Sensor Systems (MASS), Oct. 2004.
[3] S. Ren, Q. Li, H. Wang, X. Chen, and X. Zhang, “Design and Analysis of Sensing Scheduling Algorithms under Partial Coverage for Object Detection in Sensor Networks,” IEEE Trans. Parallel and Distributed Systems, vol. 18, no. 3, pp. 334-350, Mar. 2007.
[4] S. Banerjee, C. Grosan, A. Abraham, and P. Mahanti, “Intrusion Detection on Sensor Networks Using Emotional Ants,” Int’l J. Applied Science and Computations, vol. 12, no. 3, pp. 152-173, 2005.
[5] S. Capkun, M. Hamdi, and J. Hubaux, “GPS-Free Positioning in Mobile Ad-Hoc Networks,” Proc. 34th Ann. Hawaii Int’l Conf.System Sciences, Jan. 2001.
[6] N. Bulusu, J. Heidemann, and D. Estrin, “Gps-Less Low Cost Outdoor Localization for Very Small Devices,” IEEE Personal Comm. Magazine, special issue on smart spaces and environments,2000.

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