P2DF: Privacy-Preserving Data Fusion Protocol

In IoT environments, a large amount of heterogeneous data is generated from different devices in a short time. In all applications of IoT, data quality is important in decision-making. Data fusion is an approach to increase the quality of data collected from different sources and decrease the amount of wrong and conflicting data. Collecting data from different sources and fusing them has many benefits. However, there is concern about privacy violations for data owners. Designing a privacy-preserving protocol for data fusion is important. To the best of our knowledge, no protocol has been provided for private data fusion.In this paper, we propose a private protocol for data fusion in IoT environments based on the DFIOT method. The computational and communication complexity of our proposed protocol is O(n). We prove the security of our proposed protocol based on the real-ideal simulation paradigm. Also, we consider the problem of achieving security in the presence of semi-honest parties and adversaries.