针对推荐信息的不确定性，提出一种可防御诽谤攻击的数据转发机制.利用交互列表的一致性探测出恶意推荐节点的数据伪造行为，进而针对推荐信息之间的差异性，利用离群点检测方法过滤错误推荐信息，以准确地评估节点之间的信任关系；同时，根据相遇节点与目的节点的相似度准确地选择中继节点实现数据高效转发.通过仿真对比分析可知，所提出的数据转发机制相比于其他典型算法能够有效抵御节点的恶意推荐信息，同时提升数据投递率.
Data forwarding in intermittently connected wireless networks requires multiple nodes to complete in a collaborative manner. However, malicious nodes can spread false recommendation information, which is able to seriously affect the choice of relay nodes. To address this issue, this paper proposes a data forwarding mechanism that can detect the forged data produced by malicious recommendation nodes by using the consistency of interactive list. Furthermore, to aim at differences of the recommendation information, this paper filters the error recommendation information to accurately evaluate the trust relationship between two nodes by the outlier detection method. Meanwhile, this paper also achieves the efficient data forwarding by selecting the relay nodes accurately based on similarities between a meeting node and a destination node. At last, the simulation contrastive analysis shows that the proposed mechanism can resist the malicious recommendation information effectively and improve the data delivery rate compared with other typical algorithms.
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