计算机应用 ›› 2015, Vol. 35 ›› Issue (3): 746-750.DOI: 10.11772/j.issn.1001-9081.2015.03.746

• 信息安全 • 上一篇    下一篇

信任路径的过滤性搜索算法

丛丽萍, 童向荣, 姜先旭   

  1. 烟台大学 计算机与控制工程学院, 山东 烟台 264005
  • 收稿日期:2014-10-08 修回日期:2014-11-11 出版日期:2015-03-10 发布日期:2015-03-13
  • 通讯作者: 童向荣
  • 作者简介:丛丽萍(1989-),女,山东招远人,硕士研究生,CCF会员,主要研究方向:多Agent系统、信任计算;童向荣(1975-),男,山东招远人,副教授,博士,主要研究方向:多Agent系统、数据挖掘;姜先旭(1991-),男,山东即墨人,硕士研究生,主要研究方向:多Agent系统、信息传播、博弈论
  • 基金资助:

    国家自然科学基金资助项目(61170224);山东省自然科学基金资助项目(ZR2012FL07);山东省科技发展计划项目(2012GGB01017);山东省教育厅科技计划项目(J13LN24,J11LG35);烟台大学青年基金资助项目(JS11Z8)

Searching algorithm of trust path by filtering

CONG Liping, TONG Xiangrong, JIANG Xianxu   

  1. School of Computer and Control Engineering, Yantai University, Yantai Shandong 264005, China
  • Received:2014-10-08 Revised:2014-11-11 Online:2015-03-10 Published:2015-03-13

摘要:

现有的信任模型在信任路径搜索方面存在两个方面的不足:搜索过程中影响信任值的因素考虑得尚不够全面,或者同一而论;同时,对邻居节点选取时,忽略了双方交互次数的重要性。针对以上两点问题,基于图论提出了一种路径过滤性搜索算法。该算法首先引入基于交互次数的诚实可信度,用以进一步衡量节点的可信程度,并作为搜索优先级的依据,使得搜索的优先顺序更加合理。同时基于影响节点可信度的多重因素进行过滤性搜索。通过算法分析,该算法算法复杂度(n-m)2量级,比原一般细粒度算法n2量级明显降低。实验结果表明,该算法能够更好地过滤掉恶意节点,提高信任路径搜索算法的准确性,抵制恶意节点攻击。

关键词: 分布式网络, 推荐信任, 路径搜索, 诚实可信度

Abstract:

The existed trust models have two shortages in searching the trust path:firstly, factors affecting the trust value were not considered fully in the searching, or considered the same. Meanwhile, many algorithms ignored the importance of the interaction number when searching the trust path. In view of these problems, a searching algorithm of trust path based on graph theory was proposed. The concept of probability of honesty was put forward to weigh the credibility of the node further, and as the searching priority basis, it is more reasonable in the priority searching. Meanwhile it searched by filtering and used probability of multi-factors which affect the credibility of the node. The analyses of algorithm show that the complexity of the proposed algorithm is (n-m)2 magnitude, much lower than the original fine-grained algorithm which complexity is n2 magnitude. The experimental results show that the proposed algorithm can better filter out malicious nodes, improve the accuracy of the trust path search algorithms, and resist the attacks of malicious nodes.

Key words: distributed network, recommendation trust, path searching, probability of honesty

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