An intelligent trusted edge data production method for distributed Internet of things

摘要

The rapid development of distributed edge intelligence in the Internet of things (IoT) scenarios has resulted in massive edge devices continuously generating data, leading to great pressure on traditional centralized trustworthy processing security protection systems. With the continuous enhancement of edge device computing capabilities, it is now possible to achieve the goal of trusted decision while generating edge data. Therefore, research on intelligent trusted decision methods for data production is an urgent issue to be addressed. To tackle this problem, an edge intelligent trusted decision mechanism is designed. In our trusted decision mechanism, a unified mapping model based on multidimensional attributes of edge devices is first constructed. Based on the descriptive model, three important trusted decision components (TDCs) are included: static, dynamic, and comprehensive trusted decision component (TDC). In static TDC, unidirectional and bidirectional trusted decision functions of edge devices are defined, respectively. In dynamic TDC, dynamic direct and indirect recommendation trusted decision are included. The dynamic comprehensive trusted decision is calculated by effectively weighting them. In comprehensive TDC, a particle swarm optimization algorithm is introduced to adaptively adjust the weighting factors of static and dynamic TDC, and the comprehensive trusted decision is calculated. To verify the performance of our proposed trusted decision mechanism, three broad experiments are carried out. Static and dynamic TDCs are verified on randomly generated data sets, while comprehensive TDC is verified on a real data set. The simulation results show that our static and dynamic TDCs can timely and accurately detect malicious devices. Moreover, the comprehensive TDC based on the real data set performs well on different performance measurement indicators.