Abstract
Secure data aggregation intends to reduce redundant data transmission and malicious node interference in the network. Therefore, designing secure data aggregation protocol is a crucial task in WSNs. In this paper, we have proposed a Secure Data Aggregation using Fuzzy Judgement, Pattern Category and SHAP Contribution (SDAFPS) protocol. The SDAFPS protocol involves three main phases. In the first phase, the protocol controls the topology with the selection of efficient aggregator node in every interval. The second phase uses category pattern code generation and utilization concept to reduce data size and to aggregate data. Finally, in third phase, the aggregated data are encrypted using partial equation of SHAP contribution and decrypted with SHAP contribution equation. The decrypted data are verified with dataset preserved at the sink node. The SDAFPS protocol is implemented using NS2 Simulator tool and performance of proposed protocol is compared with existing protocol and validated 18% improvement in network lifetime, 10% minimized End-to-End Delay and 14% improvement on Packet Delivery Ratio over protocol.
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This article is part of the topical collection “Cyber Security and Privacy in Communication Networks” guest edited by Rajiv Misra, RK Shyamsunder, Alexiei Dingli, Natalie Denk, Omer Rana, Alexander Pfeiffer, Ashok Patel and Nishtha Kesswani.
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Reshma, S., Shaila, K. & Venugopal, K.R. SDAFPS: Secure Data Aggregation using Fuzzy Judgement, Pattern Category and SHAP Contribution. SN COMPUT. SCI. 2, 86 (2021). https://doi.org/10.1007/s42979-021-00475-1
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DOI: https://doi.org/10.1007/s42979-021-00475-1