Trust-based situation data fusion method of distributed sensor network

Abstract

The invention relates to the field of situation data fusion of the wireless sensor network, particularly to trust-based situation data fusion method of a distributed sensor network. An event fusion center receives event occurrence states detected by all association sensing nodes, determines whether events occur or not, and adjusts credibility of the association sensing nodes; fusion centers carry out fusion processing on event data detected by all association sensing nodes; and a base station receives fusion values of all fusion centers, carries out the second fusion to obtain secondary fusion numerical values, detects consistency of the fusion centers, and issues a final fusion data result. According to the invention, steps of event detection, situation data fusion and consistency detection are carried out. Fusion weights are distributed based on credibility of the sensing nodes and the historical credibility, the time relevancy, and the data relevancy are taken into consideration. Therefore, phenomena of information concealing and false information providing can be effectively prevented; the wrong detection probability is reduced; a network performance in a state with large occupation ratio of the normal sensing node number can be improved; the fusion value is close to the actual value; and the data accuracy and reliability are improved.

Description

technical field [0001] The invention relates to the field of wireless sensor network situation data fusion, in particular to a trust-based situation data fusion method for a distributed sensor network. Background technique [0002] With the increasing demand of human beings for situational awareness in the living natural world, the integration and fusion of big data information in environmental monitoring, smart home, vehicle network, human health, and oil exploration has attracted attention and attention. Due to the wide coverage, rapid increase of network traffic, large amount of data, and frequent interaction between network resources, the future sensor network of the IoT needs situational data fusion methods for evaluation and management. [0003] Situational awareness (such as security situation) is centered on data fusion, so situational awareness depends on data fusion. The integration of P2P, MANETs, ​​Ad hoc and other types of sensor networks limited by energy and ...

AI Technical Summary

Problems solved by technology

The sum and the maximum value are used as the reference basis for fusion, and due to the lack of historical credibility and data correlation considerations, although some malicious sensor node values ​​can be eliminated, malicious sensor nodes deliberately participate in the fusion with extremely small or extremely large values. It will lead to the deviation of the benchmark average value, which will eventually cause the deviation of the fusion value and reduce the accuracy of the data

All kinds of methods generally use the summation and the maximum value as the reference basis for fusion when the malicious method is predictable, which provides convenient conditions for network attackers, and the fixed fusion weight cannot adapt to dynamically changing network data. It is easy to cause the deviation between the fusion value and the real value, and also affect the stability of the system

The existing technology lacks a consistency detection rule that specifically detects the reliability of the fusion center, thus reducing the reliability of the data

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