北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2016, Vol. 39 ›› Issue (6): 99-103,130.doi: 10.13190/j.jbupt.2016.06.019

• 研究报告 • 上一篇    下一篇

权重均衡优化的Web用户行为的信任评估

田立勤1,2, 李君建2, 毋泽南1   

  1. 1. 华北科技学院 计算机学院, 北京 101601;
    2. 青海师范大学 计算机学院, 西宁 810008
  • 收稿日期:2015-12-22 出版日期:2016-12-28 发布日期:2016-11-29
  • 作者简介:田立勤(1970-),男,教授,博士生导师,E-mail:tianliqin@tsinghua.org.cn.
  • 基金资助:
    国家自然科学基金项目(61472137);中央高校基本科研业务费专项项目(3142015022);河北省物联网数据采集与处理工程中心、青海省物联网重点实验室建设项目;河北省重点研发计划项目(16273904D);青海省重点研发项目(2016-SF-130)

Trust Evaluation of Web User Behavior with Weight Optimal Balance

TIAN Li-qin1,2, LI Jun-jian2, WU Ze-nan1   

  1. 1. School of Computer Science, North China Institute of Science and Technology, Beijing 101601, China;
    2. School of Computer Science and Technology, Qinghai Normal University, Xining 810008, China
  • Received:2015-12-22 Online:2016-12-28 Published:2016-11-29

摘要: 针对Web用户信息的安全问题,提出了一种主客观相结合的用户行为信任评估模型.通过熵权法确定客观权重,通过层次分析法确定主观权重,进一步得到优化的集成权重.通过引入基于滑动窗口的长期量化评估机制和对不同类型证据的无量纲化处理,最终计算出用户行为的信任评估值.实际应用和理论分析结果表明,该模型在满足主、客观相对平衡的优化条件下,可以更准确地得出单次和长期用户行为的信任评估值,对诸如电子商务、网络金融等关键网络应用用户行为的高可靠性判断奠定了坚实的理论和实践基础.

关键词: 用户行为信任评估, 集成权重, 滑动窗口

Abstract: Aiming at the safety problem of the web user information, proposed a subjective and objective method of user behavior trust evaluation model. Using the entropy-weight-method to calculate the objective weight and analytic-hierarchy-process to determine the subjective weight, then combining the previous two results to further calculate the integrated weights with optimal balance, also introduced long-term quantitative evaluation mechanism based on the Sliding Window. Finally, through the dimensionless treatment of various type evidences and get the final user-behavior trust evaluation value. The theoretical analysis and practical application show that the model can meet the subjective and objective relative balance optimization conditions, and can get more accurate user behavior trust evaluation value for each-time and long-time interaction. It lays the solid foundation of theory and practice for high reliable analysis of user behavior in key network application such as e-commerce and online bank.

Key words: trust evaluation of user behavior, integrated weight, sliding window

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