Abstract
Due to the technological advancements and smart deployment, wireless sensor networks (WSNs) receive much attention in numerous real-time application fields. The stringent limitations of the battery of sensor devices and dubious wireless medium incur enormous challenges in the secure data collection and routing. Integration of compressive sensing and cryptography mechanism provide an efficient paradigm for reliable and energy efficient data collection over WSNs. With the aim of reducing communication cost and resilience against different WSN security attacks, this paper proposes a paillier cryptosystem and compressive sensing based routing (PC2SR) protocol. To achieve its objective, the proposed PC2SR designs three mechanisms that are paillier cryptosystem based key distribution and management, intra-cluster data gathering, and secure data transmission. Initially, the PC2SR provides paillier security keys to each device for data authentication. Instead of providing a long term security keys among two entities, the lightweight key refreshing mechanism of paillier cryptosystem in PC2SR updates the keys over a specific time interval. Secondly, the design of the Spatio-temporal measurement matrix within the intra-cluster reduces the computation and communication costs considerably. The integration of zero noise factors with all transmitted data assists the BS in detecting and isolating malicious behaviors in the network. Thus, the PC2SR efficiently offers high security in terms of integrity and confidentiality over WSN. We compare PC2SR to existing schemes, CSDA developed in 2017 and CSHEAD in early 2021 which outperform CSDA. The new scheme PC2SR offer better performance for all KPIs and thus is the best model combining data confidentiality and attack detection in WSN






Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Babenko L, Tolomanenko E (2020) Threats to wireless sensor networks and approaches to use homomorphic encryption to secure its data. J Phys Conf Ser 1624(3):032055
Babenko LK, Tolomanenko EA (2021) Development of algorithms for data transmission in sensor networks based on fully homomorphic encryption using symmetric Kuznyechik algorithm. J Phys Conf Ser 1812(1):012034
David DDS et al (2021) Medical wireless sensor network coverage and clinical application of MRI liver disease diagnosis. Eur J Mol Clin Med 7(9):2559–2571
Fang W, Wen X, Xu J et al (2019) CSDA: a novel cluster-based secure data aggregation scheme for WSNs. Cluster Comput 22:5233–5244. https://doi.org/10.1007/s10586-017-1195-7
Gao L, Zhang G, Yu B, Qiao Z, Wang J (2020) Wearable human motion posture capture and medical health monitoring based on wireless sensor networks. Measurement 166:108252
Hsieh S-H, Hung T-H, Chun-Shien Lu, Chen Y-C, Pei S-C (2018) A secure compressive sensing-based data gathering system via cloud assistance. IEEE Access 6:31840–31853
Ifzarne S, Hafidi I, Idrissi N (2018) Homomorphic encryption for compressed sensing in wireless sensor networks. In: Proceedings of the 3rd international conference on smart city applications. Association for Computing Machinery, pp 1–6. https://doi.org/10.1145/3286606.3286857
Ifzarne S, Hafidi I, Idrissi N (2021) Secure data collection for wireless sensor network. In: Ben Ahmed M, Mellouli S, Braganca L, Anouar Abdelhakim B, Bernadetta KA (eds) Emerging trends in ICT for sustainable development. The proceedings of NICE2020 International Conference. Springer, pp 241–248
Kandris D, Nakas C, Vomvas D, Koulouras G (2020) Applications of wireless sensor networks: an up-to-date survey. Appl Syst Innov 3(1):14
Khademi Nori M, Sharifian S (2020) “EDMARA2: a hierarchical routing protocol for EH-WSNs. Wirel Netw 26(6):4303–4317. https://doi.org/10.1007/s11276-020-02328-w
Kong L, Liang H, Xiao-Yang L, Yu G, Min-You W, Xue L (2015) Privacy-preserving compressive sensing for crowdsensing based trajectory recovery. In: IEEE 35th international conference on distributed computing systems (ICDCS), Columbus, OH, USA, pp 31–40
Liu Z, Han Y-L, Yang X-Y (2019) A compressive sensing-based adaptable secure data collection scheme for distributed wireless sensor networks. Int J Distrib Sens Netw 15:1–12
See CH, Abd-Alhameed RA, Zhou D, Hu YF, Horosh-Enkov KV (2008) Measure the range of sensor networks. Microwaves & RF 47(10):69–70,72–74,76
Sekar K, Devi KS, Srinivasan P (2021) Energy efficient data gathering using spatio-temporal compressive sensing for WSNs. Wirel Pers Commun 117(2):1279–1295
Singh A, Sharma S, Singh J (2021) Nature-inspired algorithms for wireless sensor networks: a comprehensive survey. Comput Sci Rev 39:100342
Sun Z, Tao R, Xiong N, Pan X (2018) CS-PLM: compressive sensing data gathering algorithm based on packet loss matching in sensor networks. Wirel Commun Mobile Comput 2018:1–12. https://doi.org/10.1155/2018/5131949
Wang X, Zhou Q, Yuantao Gu, Tong J (2019) Compressive sensing-based data aggregation approaches for dynamic WSNs. IEEE Commun Lett 23(6):1073–1076
Wimalajeewa T, Varshney PK (2019) Application of compressive sensing techniques in distributed sensor networks: a survey. arXiv:1709.10401
Zhang P, Wang J, Guo K, Wu F, Min G (2018) Multi-functional secure data aggregation schemes for WSNs. Ad Hoc Netw 69:86–99
Zhang C, Li O, Tong X, Ke K, Li M (2019) Spatiotemporal data gathering based on compressive sensing in WSNs. IEEE Wirel Commun Lett 8(4):1252–1255
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Ifzarne, S., Hafidi, I. & Idrissi, N. Compressive sensing and paillier cryptosystem based secure data collection in WSN. J Ambient Intell Human Comput 14, 6243–6250 (2023). https://doi.org/10.1007/s12652-021-03449-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12652-021-03449-6