摘要
针对群体行为一致性的特点,给出一种基于行为一致性的共谋群体识别算法。首先采用模糊综合评判对节点行为一致性进行度量,以行为一致程度值构造节点行为相似矩阵,然后通过聚类分析得到节点分类,实现共谋群体识别。实验表明,本文算法在信任评估过程中有效过滤恶意推荐,抵制了共谋攻击,提高了网络整体可用性和服务质量。
Aiming at the consistency of clique behaviors, this paper proposes a collusion identification algorithm based on consistency of activity. In this algorithm, we evaluate the consistency degree of the network nodes＇ behaviors by fuzzy theory for constructing similarity matrix; then, we identify colluding cliques by clustering method. The simulation results show the algorithm is effective in filtering malicious recommendation and resisting collusion attack, improves the reliability and quality of service for open networks.
出处
《计算机与现代化》
2014年第5期6-9,13,共5页
Computer and Modernization
基金
国家自然科学基金资助项目(60963024)
广西自然科学基金资助项目(2013GXNSFAA019330)
广西可信软件重点实验室基金资助项目(KS201213)
关键词
共谋群体
行为一致性
模糊评判
聚类分析
colluding clique
consistency of activity
fuzzy evaluation
clustering analysis
