无线传感网络中基于信任的态势数据融合机制

针对无线传感网络中节点被俘获导致融合值偏离的问题,提出了一种基于信任的态势数据融合机制,根据历史信任与节点数据相关度,制定信任度感知规则,并分3个阶段确保数据完整性. 首先,事件检测时,运用最可信多数规则,提升事件检测的准确性;其次,数据融合时,运用数据筛选规则处理不可靠数据,提升数据可靠性;最后,一致性检测时,采用一致性检测规则,在降低通信量与计算量的同时,有效而简便地检测了融合中心一致性. 新机制能有效遏制谎报攻击,改善异常节点数占有比重大时的网络性能,让融合值更贴近真实值. 理论分析及仿真证实了新机制的可靠性与有效性.

The Mechanism of Situation Data Fusion Based on Trust in Wireless Sensor Network

To cope with the problem captured nodes causing the deviation, the situation data fusion mechanism based on trust was presented. It makes trust awareness rule based on historical trust or data correlation, and guarantees consistency in three stages. Firstly, in event detection, after collecting data, it detects events through most trust majority rule to enhance accuracy. Secondly, during data fusion, it u-ses data filter rule to improve reliability. Finally, in consistency detection, it utilizes the consistency de-tection rule to reduce communication traffic, simultaneously judging the consistence of centers. The new mechanism can suppress misrepresentation and enhance the performance when abnormity is more than normal ones. It can also reduce the deviation between real value and fusion data. Simulation verifies the reliability and validity.