计算机科学 ›› 2019, Vol. 46 ›› Issue (12): 138-147.doi: 10.11896/jsjkx.181202307
所属专题: 区块链技术
巫岱玥, 李强, 余祥, 黄郡
WU Dai-yue, LI Qiang, YU Xiang, HUANG Jun
摘要: 目前,在信任模型的信任评估过程中,评价数据的来源不统一,使得不同节点获取评价数据的能力不同,不同节点对数据的认可度也不同,从而导致计算结果精度不高且较为主观,难以作为参考。针对此问题,提出基于区块链的对等网络信任模型ChainTrust。首先,定义评价序列图,根据评估节点在网络中间接信任度的可靠程度来确定间接信任度的权重。同时,改进已有区块链结构,使用Merkle Patricia树和二叉Merkle树对评价数据进行存储,进一步提高评价数据的安全性,并给出对应的存储、读取算法。仿真与分析结果表明,ChainTrust能较好地抵御恶意攻击,有效降低共谋攻击对信任评估带来的影响,并能通过调整模型参数改变模型的敏感程度。因此,ChainTrust模型是有效的,且具有较高的灵活性和普适性。
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