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Abstract

Wireless sensor network (WSN) comprises of sensor nodes such as magnetic, thermal, infra red, and the radar is setup in a particular geographical area. These nodes are used to transmit data or packet from one node to another i.e., from sender to receiver. The capabilities of WSN include manipulating and controlling the physical and environmental entities such as – humidity, temperature, sound, pressure, light etc. Wireless Sensor Networks have various applications such as Military applications, Healthcare applications etc. and also the security of the wireless sensor network is becoming a major concern. There are various types of attacks that are performed on wireless sensor networks. So due to this it is necessary to prevent WSN against these types of attacks. The size of the sensor node is small. The sensor nodes are energy constraints. The sensor nodes can easily be operated on low power. Basically, this paper presents a system which is used to prevent WSN from various types of attacks. By using the concept of artificial intelligence, we can easily detect the malicious nodes so that we can easily prevent our secret information from malicious nodes and also on expert system is developed using C language to prevent WSN from various types of attacks.

Keywords

Wireless Sensor Network (WSN) Java Native Interface (JNI) Black hole attack Wormhole attack DOS attacks Expert system Artificial intelligence 

References

  1. 1.
    Abidin, S., Izhar, M.: Attacks on WSN and its limitations. Int. J. Comput. Sci. Eng. 5(11), 157–160 (2017)Google Scholar
  2. 2.
    Akyildiz, I.F., Su, W., Sankarasubramanium, Y., Cayirci, E.: Wireless sensor networks: a survey. Comput. Netw. 38(4), 393–422 (2002)CrossRefGoogle Scholar
  3. 3.
    Shi, E., Perrig, A.: Designing secure sensor networks. IEEE Wirel. Commun. Manag. 11(6), 38–43 (2004)CrossRefGoogle Scholar
  4. 4.
    Hu, F., Sharma, N.K.: Security consideration in ad hoc sensor networks. Ad Hoc Netw. 3(1), 69–89 (2005)CrossRefGoogle Scholar
  5. 5.
    Zhou, Y., Fang, Y., Zhang, Y.: Security wireless sensor networks: a survey. IEEE Commun. Surv. Tutor. 10(3), 6–28 (2008)CrossRefGoogle Scholar
  6. 6.
    Bulbenkiene, V., Jakovlev, S., Mumgaudis, G., Pridotkes, G.: Energy loss model in wireless sensor networks. In: Second International Conference on IEEE Digital Information Processing and Communication (ICDIPC), pp. 36–38, 10–12 July 2012Google Scholar
  7. 7.
    Dening, D.: An intrusion detection model. IEEE Trans. Softw. Eng. SE-13(2), 222–232 (1987)CrossRefGoogle Scholar
  8. 8.
    Zhang, Y., Lee, W.: Instrusion detection in wireless ad-hoc network. In: Proceeding of the 6th Annual International Conference on Mobile Computing, MobiCom 2000, pp. 275–283. ACM, New York (2000). http://doi.acm.org/10.1145/345910.345958
  9. 9.
    Deng, J., et al.: A performance evaluation of intrusion-tolerant routing in wireless sensor network. In: Zhao, F., Guibas, L. (eds.) Information Processing in Sensor Network, vol. 2634, pp. 349–364. LNCS. Springer, Heidelberg (2003).  https://doi.org/10.1007/3-540-36978-3_23CrossRefGoogle Scholar
  10. 10.
    Chou, F., Tan, J.: A majority voting scheme in wireless sensor network for detecting suspicious node. In: Second International symposium on Electronic commerce and Security, ISECS 2009, vol. 2, pp. 495–498, May 2009Google Scholar
  11. 11.
    Karlof, C., Wagner, D.: Secure routing in wireless sensor networks: attacks and countermeasure. In: Proceeding of the First IEEE International Workshop on Sensor Network Protocol and Application, pp. 113–127, May 2003Google Scholar
  12. 12.
    Weingartner, E., et al.: A performance comparison of recent network simulators. In: IEEE International Conference on Communications, ICC 2009, June 2009Google Scholar
  13. 13.
    Abidin, S., Ahuja, M., Izhar, M.: Minimizing risks in wireless sensor network. In: IEEE International Conference on Electrical, Electronics, Computers, Communication, Mechanical and Computing – EECCMC 2018. IEEE XPLORE (Part No. CFP18O37-ART), 28–29 January 2018. ISBN 978-1-5386-4304-4 and 978-1-5386-4303-7Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.HMR Institute of Technology & Management (GGSIPU)DelhiIndia

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