Visible to the public Research on the Node Information Security of WSN Based on Multi-Party Data Fusion Algorithm

TitleResearch on the Node Information Security of WSN Based on Multi-Party Data Fusion Algorithm
Publication TypeConference Paper
Year of Publication2018
AuthorsYin, H., Yin, Z., Yang, Y., Sun, J.
Conference Name2018 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)
ISBN Number978-1-5386-7839-8
KeywordsBig Data, cluster routing protocol, clustering routing protocol, compositionality, data fusion technology, Human Behavior, human factors, multiparty data fusion algorithm, Network topology, node information security, plane routing protocol, power system reliability, power system security, pubcrawl, resilience, Resiliency, Routing, Routing protocols, routing security, sensor fusion, Smart Grid Sensors, Smart grids, smart power grid, smart power grids, telecommunication network reliability, telecommunication network topology, telecommunication security, urban power industry, Wireless communication, Wireless Sensor Network, Wireless sensor networks, WSN
Abstract

Smart grid is the cornerstone of the modern urban construction, leading the development trend of the urban power industry. Wireless sensor network (WSN) is widely used in smart power grid. It mainly covers two routing methods, the plane routing protocol and the clustering routing protocol. Since the plane routing protocol needs to maintain a large routing table and works with a poor scalability, it will increase the overall cost of the system in practical use. Therefore, in this paper, the clustering routing protocol is selected to achieve a better operation performance of the wireless sensor network. In order to enhance the reliability of the routing security, the data fusion technology is also utilized. Based on this method, the rationality of the topology structure of the smart grid and the security of the node information can be effectively improved.

URLhttps://cps-vo.org/node/56854
DOI10.1109/QRS-C.2018.00076
Citation Keyyin_research_2018