detection of misbehavioral activity as copy cat nodes in wireless sensor networks to enhance the network security
DHIVYA BHARATHI J,BRINDHA P,SATHYA S,SURESH S
Published in International Journal of Advanced Research in Computer Science Engineering and Information Technology
ISSN: 2321-3337 Impact Factor:1.521 Volume:6 Issue:3 Year: 26 April,2023 Pages:1809-1814
Abstract
In the existing system, wireless sensor networks have security issues such as hacking private data and node failures. From the source node, sometimes message will not be reached the destination correctly. The receiver side system may also be affected due to fake message transmission by hackers. In the proposed system we use a chord algorithm. Chord is a protocol and algorithm for a peer-to-peer distributed hash table. The Chord is used to detect the cloned node in the wide network. Rivest-Shamir-Adelman (RSA) algorithm is used to encrypt and decrypt the data at both sender and receiver nodes. The chord is used as a location algorithm. A Group leader will allocate a random number with time stamp to the available nodes in the particular network location. We have a centralized server called witness node. If same key is given by another node, the witness node identifies clone node and it terminates the transmission whether it is a fake node. With the help of RSA and chord algorithm we ensure the double protection of data from mis behavioral activity and trust to use the data fairly and responsibly.
Kewords
Distributed Hash Table, chord algorithm, RSA algorithm, witness node, random number, timestamp, encryption.
Reference
[1] Z. Zheng, A. Liu, L. X. Cai, Z. Chen, and X. Shen, “ERCD: An energy-efficient clone detection protocol in WSNs,” in Proc. IEEEINFOCOM, Apr. 14-19, 2013, pp. 2436–2444. [2] R. Lu, X. Li, X. Liang, X. Shen, and X. Lin, “GRS: The green, reliability, and security of emerging machine to machine communications,” IEEE Commun. Mag., vol. 49, no. 4, pp. 28–35, Apr. 2011. [3] I. F. Akyildiz, W. Su, Y. Sankara Subramaniam, and E. Cayirci,“Wireless sensor networks: A survey,” Computer Network., vol. 38,no. 4, pp. 393–422, Mar. 2002. [4] A. Liu, J. Ren, X. Li, Z. Chen, and X. Shen, “Design principles and improvement of cost function- based energy aware routing algorithms for wireless sensor networks,” Computer Network vol. 56,no. 7, pp. 1951– 1967, May. 2012. [5] T. Shu, M. Krunz, and S. Liu, “Secure data collection in wireless sensor networks using randomized dispersive routes,” IEEE Trans. Mobile Comput vol. 9, no. 7, pp. 941–954, Jul. 2010. [6] P. Papadimitratos, J. Luo, and J. P. Hubaux, “A randomized counter measure against parasitic adversaries in wireless sensor networks,” IEEE J. Sel. Areas Commun., vol. 28, no. 7,pp. 1036–1045, Sep. 2010. [7] R. Lu, X. Lin, T. H. Luan, X. Liang, and X. Shen, “Pseudonym changing at social spots: An effective strategy for location privacy in VANETs, “IEEE Trans. Veh. Technol., vol.61, no. 1,pp.86-96,Jan. 2012. [8] Z. M. Fadlullah, M. Fouda, N. Kato, X.Shen, and Y. Nozaki, “ An early warning system against malicious activities for smart grid communications,” IEEE Netw., vol. 25, no. 5, pp. 50-55, May. 2011.
