Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/757 2018 2018 Multi-source Heterogeneous Ecological Big Data Adaptive Fusion Method Based on Symmetric Encryption Department of Information Technology , Georgia Gwinnett College, Georgia, USA Manal .. College of Computer Information Technology, American University in the Emirates, Dubai, UAE Ahmed N. Al Al-Masri In recent years, with the rapid development of the domestic economy, the concept of sustainable development has been paid more and more attention. Ecological environment protection is more and more important, and the ecological environment is closely related to economic development. How to measure the relationship between the two is very important. Whether it is to build ecological environment protection or to ensure sustainable development of the economy, we should take the green development concept as a guiding concept, promote ecological economic development, and study the integration of ecological data is of great significance for solving these problems. The research of this thesis studies the multi-source heterogeneous (MSH) ecological big data (BD)adaptive fusion based (FM) based on symmetric encryption. This paper sets up a comparative experiment, multi-sensor (MS) data fusion based (DFM) based on Rough set theory, MSH data fusion based on data information conversion. The method is compared with the symmetric fusion MSH BD adaptive FM proposed in this paper. The results show that the MSH DFM based on Rough set theory has the highest confidence of 0.812; the MSH DFM based on data information conversion has the highest confidence of 0.68; based on symmetric encryption MSH BD The fusion confidence of the adaptive FM is up to 0.965, and the MSH ecological BD adaptive FM based on symmetric encryption is superior. 2021 2021 08 20 10.54216/FPA.050101 https://www.americaspg.com/articleinfo/3/show/757