International Journal of Computer Networks and Applications

Open Access Open Access  Restricted Access Subscription Access

Source Location Privacy for Geographical Routing in Wireless Sensor Networks: SLPGR


Affiliations
1 Department of Computer Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bangalore, Karnataka, India
 

Challenges in the military, environment, medical, industrial, home, traffic applications, and agriculture extend the scope of Wireless Sensor Networks. Data security over wireless networks is a challenge because of the presence of malicious and non-malicious users, whose purpose is to intercept communication or prevent the transmission of data by real users to perform data theft. To improve the location privacy in geographical routing, a hash-based location privacy-preserving scheme and fake source identification in grid-based geographical routing protocol in WSN are presented. In the SLPGR approach, SHA-256 hash encoding is implemented which hides the location information from attackers. The proposed fake source identification guarantees that the fake source and real source nodes are situated on different quadrants and have enough distance between them. The Findings indicate that the SLPGR model’s packet delivery ratio is further 278 % enhancement contrast to the tree-based diversionary routing, and more than 38 % compared to the CASER random walking system. The safety duration of the proposed method increases approx. 13% more than the tree-based diversionary routing and 11% more than CASER random walk routing. Energy consumption of the proposed method is lower by 3 times than the tree-based diversionary routing method, 1.4 times lower than CASER random walk routing. The comparative analysis of the SLPGR method shows 3 times lesser delivery miss ratio than tree-based devolutionary routing and 2.6 times lesser delivery miss ratio than CASER routing scheme.

Keywords

Fake Source, Wireless Sensor Networks, Source Location Privacy, Geographical Routing, SHA-256.
User
Notifications
Font Size

  • Naghibi, Maryam and H. Barati. “EGRPM: Energy efficient geographic routing protocol based on mobile sink in wireless sensor networks.” Sustain. Comput. Informatics Syst. 25 (2020): 100377.

  • Ahmad Raza Hameed, Saif ul Islam, Mohsin Raza, Hasan Ali Khattak, Towards Energy and Performance-aware Geographic Routing for IoT-enabled Sensor Networks, Computers & Electrical Engineering, Volume 85, 2020, 106643.

  • Z. Qian, Q. Xiaolin, and D. Youwei, “Intelligent silent zone for source-location privacy based on context-awareness in WSNs,” Transactions of Nanjing University of Aeronautics and Astronautics, vol. 35, no. 1, pp. 203–218, 2018.

  • C. Gu, M. Bradbury, J. Kirton, and A. Jhumka, “A decision theoretic framework for selecting source location privacy aware routing protocols in wireless sensor networks,” Future Generation Computer Systems, vol. 87, pp. 514–526, 2018.

  • H. Wang, G. Han, W. Zhang, M. Guizani and S. Chan, "A Probabilistic Source Location Privacy Protection Scheme in Wireless Sensor Networks," in IEEE Transactions on Vehicular Technology, 68, 6, pp. 5917-5927, June 2019..

  • R. Rios, and J. Lopez, “Analysis of Location Privacy Solutions in Wireless Sensor Networks”, IET Communications, vol. 5, pp. 2518 - 2532, 2014.

  • Mutalemwa, L.C.; Shin, S. Secure Routing Protocols for Source Node Privacy Protection in Multi-Hop Communication Wireless Networks. Energies 2020, 13, 292. https://doi.org/10.3390/en13020292

  • Jinfang Jiang, Guangjie Han, Hao Wang, Mohsen Guizani, A survey on location privacy protection in Wireless Sensor Networks, Journal of Network and Computer Applications, Volume 125,2019, Pages 93-114. https://doi.org/10.1016/j.jnca.2018.10.008

  • Nidhi Sharma, Ravindra Bhatt, Privacy Preservation in WSN for Healthcare Application, Procedia Computer Science, Volume 132, 2018, Pages 1243-1252, ISSN 1877-0509. https://doi.org/10.1016/j.procs.2018.05.040

  • L.C. Mutalemwa, S. Shin Achieving source location privacy protection in monitoring wireless sensor networks through proxy node routing Sensors, 19 (2019), p. 1037, https://doi.org/10.3390/s19051037

  • Tang, D., Li, T., Ren, J., & Wu, J. Cost-Aware Secure Routing (CASER) Protocol Design for Wireless Sensor Networks. IEEE Transactions on Parallel and Distributed Systems, 26, 960-973, 2015. https://doi.org/10.1109/TPDS.2014.2318296

  • Long, J.; Dong, M.; Ota, K.; Liu, A. Achieving source location privacy and network lifetime maximization through tree-based diversionary routing in wireless sensor networks. IEEE Access 2014, 2, 633–651. https://doi.org/10.1109/ACCESS.2014.2332817

  • N. Jan and S. Khan, Energy-Efficient Source Location Privacy Protection for Network Lifetime Maximization Against Local Eavesdropper in Wireless Sensor Network (EeSP). Hoboken, NJ, USA: Wiley, Aug. 2019

  • Manivannan D., Moni S.S., Zeadally S. Secure authentication and privacy-preserving techniques in Vehicular Ad-hoc NETworks (VANETs). Veh. Commun., 25 (2020)

  • L. Lightfoot, Y Li, J. Ren. STaR: design and quantitative measurement of source-location privacy for wireless sensor networks. Security and Communication Networks. 2016, 9(3): 220-228. https://doi.org/10.1002/sec.527

  • Mutalemwa, L.C.; Shin, S. Strategic Location-Based Random Routing for Source Location Privacy in Wireless Sensor Networks. Sensors 2018, 18, 2291. https://doi.org/10.3390/s18072291

  • Bradbury, M.; Jhumka, A.; Leeke, M. Hybrid online protocols for source location privacy in wireless sensor networks. J. Parallel Distrib. Comput. 2018, 115, 67–81.

  • Al-Mistarihi MF, Tanash IM, Yaseen FS et al (2020) Protecting source location privacy in a clustered wireless sensor networks against local eavesdroppers. Mob NetwAppl 25:42–54

  • D. R. Manjunath and S. N. Thimmaraju, "A blind path geographical energy aware routing protocol for wireless sensor networks," 2019 1st International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE), Bangalore, India, 2019, pp. 196-200, doi: 10.1109/ICATIECE45860.2019.9063840.

  • Jan N, Al-Bayatti AH, Alalwan N, Alzahrani AI. An Enhanced Source Location Privacy based on Data Dissemination in Wireless Sensor Networks (DeLP). Sensors (Basel). 2019;19(9):2050.doi:10.3390/s19092050. https://doi.org/10.3390/s19092050.


Abstract Views: 353

PDF Views: 2




  • Source Location Privacy for Geographical Routing in Wireless Sensor Networks: SLPGR

Abstract Views: 353  |  PDF Views: 2

Authors

Manjunath D R
Department of Computer Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bangalore, Karnataka, India
Anil Kumar B
Department of Computer Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bangalore, Karnataka, India

Abstract


Challenges in the military, environment, medical, industrial, home, traffic applications, and agriculture extend the scope of Wireless Sensor Networks. Data security over wireless networks is a challenge because of the presence of malicious and non-malicious users, whose purpose is to intercept communication or prevent the transmission of data by real users to perform data theft. To improve the location privacy in geographical routing, a hash-based location privacy-preserving scheme and fake source identification in grid-based geographical routing protocol in WSN are presented. In the SLPGR approach, SHA-256 hash encoding is implemented which hides the location information from attackers. The proposed fake source identification guarantees that the fake source and real source nodes are situated on different quadrants and have enough distance between them. The Findings indicate that the SLPGR model’s packet delivery ratio is further 278 % enhancement contrast to the tree-based diversionary routing, and more than 38 % compared to the CASER random walking system. The safety duration of the proposed method increases approx. 13% more than the tree-based diversionary routing and 11% more than CASER random walk routing. Energy consumption of the proposed method is lower by 3 times than the tree-based diversionary routing method, 1.4 times lower than CASER random walk routing. The comparative analysis of the SLPGR method shows 3 times lesser delivery miss ratio than tree-based devolutionary routing and 2.6 times lesser delivery miss ratio than CASER routing scheme.

Keywords


Fake Source, Wireless Sensor Networks, Source Location Privacy, Geographical Routing, SHA-256.

References





DOI: https://doi.org/10.22247/ijcna%2F2021%2F209708