Low-Complexity Security Algorithm Again Black-hole Attacking Node Considering Energy Balance for WSNs
Abstract
Wireless sensor network (WSN) is a network through radio waves to link a large number of unevenly distributed nodes on a wide range of areas for the purpose of sensing, processing and collecting data.The data transmitted in WSNs is usually sensitive that needs to be protected. WSNs are more vulnerable to attacks due to network characteristics such as wireless transmission, changing network topologies, computing power, limited memory and power of nodes comparing to wired networks. There are many types of attacks on WSNs such as sinkhole attacks, data integrity attacks, wormhole attacks, Black hole attacks, etc. In this article, we will evaluate the impact of Black-hole attacks in the WSN network when using the AODV routing protocol (Ad-hoc On-demand Distance Vector routing). The Black hole attack model will be simulated by Network Simulator 2 (NS-2) by the number of lost packets by counting the number of packets sent by the sending node, receiving packets to destination, and rest energy of the nodes in two cases.
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References
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[3] D. Buch, , and D. Jinwala, “Prevention of wormhole attack in wireless sensor network,” International Journal of Network Security and Its Applications (IJNSA), vol. 3, no. 5, pp. 85–98, 2011.
[4] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “Security issues in wireless sensor network data gathering protocols: a survey,” Computer Networks, vol. 38, no. 4, pp. 393–422, 2002.
[5] H. Deng, W. Li, and D. Agrawal, “Routing security in wireless ad hoc networks,” in IEEE Communications Magazine, Oct. 2002, pp. 70–75.
[6] J. H. et al., “System architecture directions for networked sensors,” in Proc. 9th Int’l. Conf. Architectural Support for Programming Languages and Operating Systems, 2000, pp. 93–104.
[7] K. Xing, S. S. R. Srinivasan, M. J. M. Rivera, and J. L. Cheng, Attacks and Countermeasures in Sensor Networks: A Survey. Network Security Springer, 2010, pp. 251–272.
[8] S. Dokurer, Y. M. Erten, and C. E. Acar, “Performance analysis of ad-hoc networks under black hole attacks,” in Proceedings 2007 IEEE SoutheastCon, March 2007, pp. 148–153.
[9] M. Prahubhudutta, P. Sangram, S. Nityananda, and S. S. Satapathy, “Security issues in wireless sensor network data gathering protocols: a survey,” Journal of Theoretical and Applied Information Technology, vol. 13, no. 4, pp. 14–27, 2010.
[10] G. Shobha, R. R. Chittal, and K. Kumar, “Medical applications of wireless networks,” in International Conference on Systems and Networks Communications, 2007, pp. 1–12.
[11] R. Sumathi and M. G. Srinivas, “A survey of qos based routing protocols for wireless sensor networks,” Journal of Information Processing Systems, vol. 8, no. 4, pp. 589–602, 2012.
[12] S. Ramaswamy, H. Fu, M. Sreekantaradhya, J. Dixon, and K. Nygard, “Prevention of cooperative e black hole attack in wireless ad hoc networks,” in Department of Computer Science, 2003, retrieved from official website: www.cs.ndsu.nodak.edu/ nygard/research/BlackHoleMANET.pdf 2003.
[13] S. Dokurer, Simulation of Black hole attack in wireless Ad hoc networks. Atihm University: Thesis Master in Computer Engineering, 2006, p. 78.
[14] V. Khandelwal and D. Goyal, “Blackhole attack and detection method for aodv routing protocol in manets,” International Journal of Advanced Research in Computer Engineering and Technology (IJARCET), vol. 2, no. 4, pp. 89–868, April 2013.
[15] V. Kumar, A. Jain, and P. N. Barwal, “Wireless sensor networks: Security issues, challenges and solutions,” International Journal of Information and Computation Technology, vol. 4, no. 8, pp. 859–868, Dec. 2014.
[16] J. Al-Karaki and A. Kamal, “Routing techniques in wireless sensor networks:a survey,” IEEE Wireless Communications, vol. 11, no. 6, pp. 1–15, Dec. 2004.
[17] T. N. T. Huong, H. P. Cong, T. V. Huu, and X. H. Van, “Artificial intelligence based adaptive gop size selection for effective wyner-ziv video coding,” in Intl Conf. on Advanced Technol. for Commun., 2018.
[18] X. Yu and Y. Yuan, “Hand gesture recognition based on faster-rcnn deep learning,” J. of Comput., vol. 14, no. 2, pp. 101–110, Feb. 2019.
[19] P. N. Huu, V. Tran-Quang, and T. Miyoshi, “Low-complexity and energy-efficient algorithms on image compression for wireless sensor networks,” IEICE Transactions on Communications, vol. E93-B, no. 12, pp. 3438–3447, Dec. 2010.
[20] T. N. Duong, V. D. Than, T. H. Tran, Q. H. Dang, D. M. Nguyen, and H. M. Pham, “An effective similarity measure for neighborhood-based collaborative filtering,” in 5th NAFOSTED Conf. on Infor. and Comput. Scie. (NICS 2018), Nov. 2018, pp. 250–254.
[21] P. N. Huu, V. Tran-Quang, and T.Miyoshi, “Multi-hop reed-solomon encoding scheme for image transmission on wireless sensor networks,” in Proceedings of 4th Intl Conf. Commun. Electron. (ICCE 2012), Aug. 2012, pp. 74–79.
[22] J. K. Choi, V. D. Nguyen, H. N. Nguyen, V. V. Duong, T. H. Nguyen, H. Cho, H.-K. Choi, and S.-G. Park, “A time-domain estimation method of rapidly time-varying channels for ofdm-based lte-r systems,” Digital Commun. and Netw., vol. 5, no. 2, pp. 94–101, May 2019.
Published
2020-04-30
How to Cite
NGUYEN HUU, Phat.
Low-Complexity Security Algorithm Again Black-hole Attacking Node Considering Energy Balance for WSNs.
Journal of Science and Technology: Issue on Information and Communications Technology, [S.l.], v. 18, n. 4.2, p. 26-31, apr. 2020.
ISSN 1859-1531.
Available at: <http://ict.jst.udn.vn/index.php/jst/article/view/86>. Date accessed: 24 apr. 2024.
doi: https://doi.org/10.31130/ict-ud.2020.86.
Section
Articles
