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。
At present,in the process of trust evaluation of trust model,because the sources of evaluation data are not uniform,the ability of different nodes to obtain evaluation data is different,and the recognition degree of different nodes to data is also different,the computational results are low accuracy,subjective and difficult to be used as a reference.Aiming at these problems,this paper proposed a blockchain-based peer-to-peer network trust model,named ChainTrust.The evaluation sequence graph is defined.The indirect trust weight is determined according to the reliability of the indirect trust degree of the evaluation node.Meanwhile,this paper improved the current blockchain structure,by using the Merkle Patricia tree and the binary Merkle tree to store the evaluation data,and gave the corresponding storing and reading algorithms.Simulation and analysis results show that ChainTrust can better resist a variety of malicious attacks,thus reducing the impact from the collusion attack,changing the sensitivity of the model by adjusting the model parameters.Therefore,ChainTrust is effective and has high flexibility and universality.
作者
巫岱玥
李强
余祥
黄郡
WU Dai-yue;LI Qiang;YU Xiang;HUANG Jun(National University of Defense Technology,Hefei 230037,China)
出处
《计算机科学》
CSCD
北大核心
2019年第12期138-147,共10页
Computer Science
基金
国防科技大学科研基金项目(KYJ2017J351)资助
作者简介
巫岱玥(1994-),男,主要研究方向为区块链、信息安全;通信作者:李强(1962-),男,教授,硕士生导师,主要研究方向为区块链、软件工程、信息安全,E-mail:lychfeei@163.com;余祥(1986-),男,博士生,讲师,主要研究方向为信息安全;黄郡(1983-),男,博士,讲师,主要研究方向为信息安全。
