Energy Efficient Secured PSO Optimized Clustering and Data Aggregation Routing Protocol for Wireless Sensor Networks

Authors

  • Yesodha K Hindustan Institute of Technology and Science Author
  • Krishnamurthy M KCG College of Technology, Chennai, Tamil Nadu Author
  • Selvi M Vellore Institute of Technology, Vellore, Tamil Nadu Author
  • Thangaramya K Vellore Institute of Technology, Vellore, Tamil Nadu Author
  • Santhosh Kumar SVN Vellore Institute of Technology, Vellore, Tamil Nadu Author
  • Kannan Arputharaj Anna University, Chennai, Tamil Nadu Author

DOI:

https://doi.org/10.70339/kpwdjn50

Keywords:

Data Aggregation, Security, Energy Efficiency, Routing, Attacks, False data injection.

Abstract

In Wireless Sensor Networks (WSNs), sensor nodes are placed to sense and collect data.  Due to the energy constraint nature of WSN, optimising the energy during the data dissemination is a major concern. To solve this problem, data aggregation may be used to bring down the redundant transmission of packets in WSN. In most of the previously available techniques, security is also a major concern during data aggregation and routing process with optimized energy.  Many data aggregation-based routing systems are subject to security attacks during the data transfer from sensors to source to Clustered Heads (CHs) and then to sink with data aggregation process. Moreover, the existing data aggregation-based routing protocols suffer from data redundancy with less accuracy in aggregated data. For handling such issues order to overcome these issues, an Energy Efficient Secured Clustered Particle Swarm Optimization (PSO) oriented Data Aggregation Routing Protocol (EESCPSO-DARP) that can provide efficient authentication during data aggregation-based routing is introduced in this paper.  Moreover, the proposed protocol enhances the rate of the data transmission by efficient prevention of false data injection and other attacks through node authentication and data encryption. This proposed protocol minimizes the energy usage by minimizing the retransmissions by eliminating the possible redundant transmissions of data during data aggregation-based routing. Moreover, the introduced protocol minimizes both communication and computational overhead through optimal clustering and routing with PSO and provides and efficient routing system. This proposed EESCPSO-DARP protocol has been developed by using the NS3 simulator. The results of this protocol showed improved security, higher packet delivery ratio and enhanced network throughput with reduced energy and delay.

References

Jin Y, Kwak K S, and Yoo S J, 2020, “A novel energy supply strategy for stable sensor data delivery in wireless sensor networks” ,IEEE Systems. Journal., vol. 14, no. 3, pp. 3418_3429.

Cengiz K and Dag T, 2018, “Energy aware multi-hop routing protocol for WSNs”, IEEE Access, vol. 6, pp. 26222633.

Das S.K and Tripathi S, 2018 ``Intelligent energy-aware efficient routing for MANET,'' Wireless Networks., vol. 24, no. 4, pp. 1159.

Sasirekha S and Swamynathan S, 2017, ``Cluster-chain mobile agent routing algorithm for efficient data aggregation in wireless sensor network,'' Journal of Communication. Networks., vol. 19, no. 4, pp. 392-401.

Haseeb K, Islam N, Saba T, Rehman A, and Mehmood Z, 2020, ``LSDAR: A light-weight structure-based data aggregation routing protocol with secure Internet of Things integrated next-generation sensor networks,'' Sustain. Cities Soc., vol. 54, pp. 1-9.

Thangaramya K, Kulothungan K, Logambigai R, Selvi M, Ganapathy S, and Kannan A, 2019, ``Energy aware cluster and neuro-fuzzy based routing algorithm for wireless sensor networks in IoT,'' Computer Networks., vol. 151, pp. 211-223.

Lee J S and Teng C L, 2017, ``An enhanced hierarchical clustering approach for mobile sensor networks using fuzzy inference systems,'' IEEE Internet Things J., vol. 4, no. 4, pp. 1095-1103.

El Alami H and Najid A, 2019, ``ECH: An enhanced clustering hierarchy approach to maximize lifetime of wireless sensor networks,'' IEEE Access, vol. 7, pp. 107142-107153.

Rajasoundaran S, Kumar SVN, Selvi M, Ganapathy S, Rakesh R, Kannan A, 2021,” Machine learning based volatile block chain construction for secure routing in decentralized military sensor networks”, Wireless Networks, vol 27 (7), pp. 4513-4534.

Santhosh Kumar SVN, Yogesh Palanichamy, Selvi M, Sannasi Ganapathy, Arputharaj Kannan, Sankar Pariserum Perumal, 2021,” Energy efficient secured K means based unequal fuzzy clustering algorithm for efficient reprogramming in wireless sensor networks”, wireless networks, vol 27, pp. 3873-3894.

Munuswamy Selvi, SVN Santhosh Kumar, Sannasi Ganapathy, AyyasamyAyyanar, Harichandran Khanna Nehemiah, Arputharaj Kannan, 2021,” energy efficient clustered gravitational and fuzzy based routing algorithm in WSNs”. Wireless Personal Communications, vol 116 (1).

Yesodha, K., Krishnamurthy, M., Thangaramya, K. and Kannan, A., 2024. Elliptic curve encryption-based energy-efficient secured ACO routing protocol for wireless sensor networks. The Journal of Supercomputing, Vol. 80, pp. 18866–18899.

Jasper J, 2021, “A secure routing scheme to mitigate attack in wireless ad hoc sensor network”, Computers & Security: Elsevier, vol.103, pp:102197.

Kowsalya R, Jeetha BR, 2021, “Cluster based data-aggregation using lightweight cryptographic algorithm for wireless sensor networks”, Materials Today: Proceedings: Elsevier.

Hassan A, Anter A, Kayed M, 2021, “A robust clustering approach for extending the lifetime of wireless sensor networks in an optimized manner with a novel fitness function”, Sustainable Computing: Informatics and Systems: Elsevier, vol.30, pp:100482.

Maheswari M, Karthika R A, 2021, “A Novel QoS Based Secure Unequal Clustering Protocol with Intrusion Detection System in Wireless Sensor Networks”, Wireless Personal Communications: Springer, vol.118(2), pp:1535-57.

Mosavifard A, Barati H. A, 2020, “An energy-aware clustering and two-level routing method in wireless sensor networks”, Computing: Springer vol.102(7), pp:1653-71

Bongale AM, Nirmala CR, Bongale AM, 2020, “Energy efficient intra cluster data aggregation technique for wireless sensor network”, International Journal of Information Technology: Springer. Vol. 27, pp.1-9.

Deebak BD, Al-Turjman F, 2020, “A hybrid secure routing and monitoring mechanism in IoT-based wireless sensor networks”, Ad Hoc Networks: Elsevier, vol. 97, pp:102022.

Saidi A, Benahmed K, Seddiki N, 2020, “Secure cluster head election algorithm and misbehaviour detection approach based on trust management technique for clustered wireless sensor networks”, Ad Hoc Networks: Elsevier, vol.106, pp:102215.

Revanesh M, Sridhar V, Acken JM, 2020, “Secure Coronas Based Zone Clustering and Routing Model for Distributed Wireless Sensor Networks”, Wireless Personal Communications: Springer, vol. 112(3), pp:1829-57.

Zhang, Y., Zhang, X., Ning, S., Gao, J., & Liu, Y. 2019, “Energy-efficient multilevel heterogeneous routing protocol for wireless sensor networks”, IEEE Access, 7, pp.55873-55884.

Mehetre DC, Roslin SE, Wagh SJ, 2019, “Detection and prevention of black hole and selective forwarding attack in clustered WSN with Active Trust”, Cluster Computing: Springer. Vol.22(1), pp:1313-28.

Hongjuan Li, Kai Lin, Keqiu Li, 2011,” Energy-efficient and high-accuracy secure data aggregation in wireless sensor networks”, computer communications, vol.34, pp. 591-597.

Ahmed, Saidi, Khelifa Benahmed, and Nouredine Seddiki. "Secure cluster head election algorithm and misbehaviour detection approach based on trust management technique for clustered wireless sensor networks." Ad Hoc Networks, vol.106, 2020 pp:102215.

Ahmed Abdulhadi, Jasim, Mohd Yamani Idna Bin Idris, Saadial Razalli Bin Azzuhri, Noor Riyadh Issa, Noorzaily Bin Mohamed Noor, Jagadeesh Kakarla, and Iraj Sadegh Amiri. "Secure and energy-efficient data aggregation method based on an access control model." IEEE Access, vol.7, 2019, pp:164327-164343.

Osama A. Khashan a,, Rami Ahmad Nour M. Khafajah, 2021, “An automated lightweight encryption scheme for secure and energy-efficient communication in wireless sensor networks”, ad hoc networks, vol 115.

Wei Fang · XueZhi Wen · Jiang Xu1 · JieZhong Zhu, 2019, “CSDA: a novel cluster-based secure data aggregation scheme for WSNs, “Cluster Computing, vol. 22, pp. 5233- 5244.

Haseeb, Khalid, Naveed Islam, Tanzila Saba, Amjad Rehman, and Zahid Mehmood, 2020, "LSDAR: A light-weight structure-based data aggregation routing protocol with secure internet of things integrated next-generation sensor networks." Sustainable Cities and Society 54, 101995.

Hu, Peng, Xixi Chu, LaishuiLv, Kaizhong Zuo, Tianjiao Ni, Taochun Wang, and Zhangyi Shen. 2023, "An efficient and secure data collection scheme for predictive maintenance of vehicles." Ad Hoc Networks vol.146, pp.103157.

Wu, Qiyu, Fucai Zhou, Jian Xu, Qiang Wang, and Da Feng, 2022, "Secure and efficient multifunctional data aggregation without trusted authority in edge-enhanced IoT." Journal of Information Security and Applications vol.69, pp.103270.

Alghamdi, Wael Y, 2023, "Designing A Secure and Long-Lived WSN for Data Collection." Procedia Computer Science 220 pp. 187-194.

Dorsala, Mallikarjun Reddy, V. N. Sastry, and Sudhakar Chapram, 2022, "Fair payments for privacy-preserving aggregation of mobile crowdsensing data." Journal of King Saud University-Computer and Information Sciences 34, no. 8,pp.5478-5492.

Khan, H.M., Khan, A., Jabeen, F., Anjum, A. and Jeon, G., 2021. Fog-enabled secure multiparty computation-based aggregation scheme in smart grid. Computers & Electrical Engineering, 94, p.107358.

Sindhuja, M., Vidhya, S., Jayasri, B.S. and Shajin, F.H., 2023. Multi-objective cluster head using self-attention based progressive generative adversarial network for secured data aggregation. Ad Hoc Networks, 140, p.103037.

Regueiro, C., Seco, I., de Diego, S., Lage, O. and Etxebarria, L., 2021. Privacy-enhancing distributed protocol for data aggregation based on blockchain and homomorphic encryption. Information Processing & Management, 58(6), p.102745.

Othman, S.B., Almalki, F.A., Chakraborty, C. and Sakli, H., 2022. Privacy-preserving aware data aggregation for IoT-based healthcare with green computing technologies. Computers and Electrical Engineering, 101, p.108025.

Shen, X., Zhu, L., Xu, C., Sharif, K. and Lu, R., 2020. A privacy-preserving data aggregation scheme for dynamic groups in fog computing. Information Sciences, 514, pp.118-130.

Ravi, G., Das, M.S. and Karmakonda, K., 2023. Reliable cluster-based data aggregation scheme for IoT network using hybrid deep learning techniques. Measurement: Sensors, 27, p.100744.

Gao, Y., Li, Q., Zheng, Y., Wang, G., Wei, J. and Su, M., 2022. SEDML: Securely and efficiently harnessing distributed knowledge in machine learning. Computers & Security, 121, p.102857.

Lu, S., Li, R., Liu, W., Guan, C. and Yang, X., 2023. Top-k sparsification with secure aggregation for privacy-preserving federated learning. Computers & Security, 124, p.102993.

Anitha, S., Saravanan, S. and Chandrasekar, A., 2023. Trust management based multidimensional secure cluster with RSA cryptography algorithm in WSN for secure data transmission. Measurement: Sensors, p.100889.

Liu, X., Yu, J., Yu, K., Wang, G. and Feng, X., 2022. Trust secure data aggregation in WSN-based IIoT with single mobile sink. Ad Hoc Networks, 136, p.102956.

Lin, H., Garg, S., Hu, J., Kaddoum, G., Peng, M. and Hossain, M.S., 2020. A blockchain-based secure data aggregation strategy using sixth generation enabled network-in-box for industrial applications. IEEE Transactions on Industrial Informatics, 17(10), pp.7204-7212.

Shim, K.A. and Park, C.M., 2014. A secure data aggregation scheme based on appropriate cryptographic primitives in heterogeneous wireless sensor networks. IEEE transactions on parallel and distributed systems, 26(8), pp.2128-2139.

Xue, K., Zhu, B., Yang, Q., Wei, D.S. and Guizani, M., 2019. An efficient and robust data aggregation scheme without a trusted authority for smart grid. IEEE Internet of Things Journal, 7(3), pp.1949-1959.

Rezaeibagha, F., Mu, Y., Huang, K. and Chen, L., 2020. Secure and efficient data aggregation for IoT monitoring systems. IEEE Internet of Things Journal, 8(10), pp.8056-8063.

Jasim, A.A., Idris, M.Y.I.B., Azzuhri, S.R.B., Issa, N.R., Noor, N.B.M., Kakarla, J. and Amiri, I.S., 2019. Secure and energy-efficient data aggregation method based on an access control model. IEEE Access, 7, pp.164327-164343.

Zhang, J. and Dong, C., 2022. Secure and lightweight data aggregation scheme for anonymous multi-receivers in WBAN. IEEE Transactions on Network Science and Engineering, 10(1), pp.81-91.

Rezvani, M., Ignjatovic, A., Bertino, E. and Jha, S., 2014. Secure data aggregation technique for wireless sensor networks in the presence of collusion attacks. IEEE transactions on Dependable and Secure Computing, 12(1), pp.98-110.

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Published

2024-09-30

How to Cite

Energy Efficient Secured PSO Optimized Clustering and Data Aggregation Routing Protocol for Wireless Sensor Networks. (2024). International Journal of Global Perspectives in Academic Research, 1(2). https://doi.org/10.70339/kpwdjn50