User's Behavior Trust Evaluate Algorithm Based On Cloud Model

被引:5
|
作者
Li Jun-Jian [1 ]
Tian Li-Qin [2 ]
机构
[1] Qinghai Normal Univ, Coll Comp, Xining, Qinghai, Peoples R China
[2] North China Inst Sci & Technol, Dept Comp, Beijing East, Peoples R China
来源
2015 FIFTH INTERNATIONAL CONFERENCE ON INSTRUMENTATION AND MEASUREMENT, COMPUTER, COMMUNICATION AND CONTROL (IMCCC) | 2015年
关键词
Cloud Computing; User's Behavior; Dynamic Trust Evaluation;
D O I
10.1109/IMCCC.2015.123
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cloud computing is developing rapidly and the open environment in cloud computing is much more complex and unpredictable than other applications, so just providing the identity certification cannot ensure the security of cloud user and cloud service provider, in order to find a effective way to ensure cloud security, we have to solve the problem of trustiness of cloud user's behavior first, in this paper, we propose a dynamic trust evaluate method to deal with cloud user's bahavior, through using Entropy Method to reflect the essential regular patterm of user's behavior evidence, making the evaluate way become a dynamic model, weaken the subjectivity of simply using AHP, moreover, still need AHP to make the result fit people's subjective experience, so we also put forward a integrate algorithm that combine Entropy Method and AHP, in this way, the final evaluate value will keep the balance between objective and subjective and provide quantitative analysis foundation for security control, The simulation shows that the dynamic trust evaluate method can effectively distinguish user's abnormal behavior.
引用
收藏
页码:555 / 560
页数:6
相关论文
共 50 条
  • [41] Cloud service qos prediction algorithm based on time perception and user’s interest
    Zhou, Zhou
    Zhou, Xinyuan
    UPB Scientific Bulletin, Series C: Electrical Engineering and Computer Science, 2020, 82 (04): : 93 - 102
  • [42] CLOUD SERVICE QoS PREDICTION ALGORITHM BASED ON TIME PERCEPTION AND USER'S INTEREST
    Zhou, Zhou
    Zhou, Xinyuan
    UNIVERSITY POLITEHNICA OF BUCHAREST SCIENTIFIC BULLETIN SERIES C-ELECTRICAL ENGINEERING AND COMPUTER SCIENCE, 2020, 82 (04): : 93 - 102
  • [43] Personality Predicting Model Based on User's Linguistic Behavior
    Nie, Ying-jie
    Gao, Guo-jiang
    Wang, Yan-xin
    Liu, Duo-xing
    Gao, Kai
    2017 9TH INTERNATIONAL CONFERENCE ON MODELLING, IDENTIFICATION AND CONTROL (ICMIC 2017), 2017, : 827 - 832
  • [44] Research on the Application of User Behavior Auditing Based on Hidden Markov Model in Cloud Environment
    Zhang, Kejun
    Jiang, Chen
    Yang, Yunsong
    Wang, Yu
    Zhang, Guoliang
    3RD INTERNATIONAL CONFERENCE ON MATERIALS SCIENCE AND MECHANICAL ENGINEERING, (ICMSME 2016), 2016, : 125 - 129
  • [45] TRUST-CAP: A Trust Model for Cloud-based Applications
    AbdAllah, Eslam G.
    Zulkernine, Mohammad
    Gu, Yuan Xiang
    Liem, Clifford
    2017 IEEE 41ST ANNUAL COMPUTER SOFTWARE AND APPLICATIONS CONFERENCE (COMPSAC), VOL 2, 2017, : 584 - 589
  • [46] Semantic representation of user's mental trust model
    Mahmood, Omer
    Haynes, John D.
    ADVANCES AND INNOVATIONS IN SYSTEMS, COMPUTING SCIENCES AND SOFTWARE ENGINEERING, 2007, : 345 - 350
  • [47] A User Trust-Based Collaborative Filtering Recommendation Algorithm
    Zhang, Fuzhi
    Bai, Long
    Gao, Feng
    INFORMATION AND COMMUNICATIONS SECURITY, PROCEEDINGS, 2009, 5927 : 411 - 424
  • [48] Hybrid Recommendation Algorithm Based on Trust Relationship and User Preference
    Dong, Wu
    Yi, Cai
    Kai, Yang
    PROCEEDINGS OF 2017 IEEE 7TH INTERNATIONAL CONFERENCE ON ELECTRONICS INFORMATION AND EMERGENCY COMMUNICATION (ICEIEC), 2017, : 429 - 433
  • [49] A Collaborative Filtering Algorithm Based on Double Clustering and User Trust
    Tang, Tonglong
    Li, Xiaoyu
    PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON SENSOR NETWORK AND COMPUTER ENGINEERING, 2016, 68 : 31 - 37
  • [50] Intelligent encryption algorithm for cloud computing user behavior feature data
    Ye, Kai
    Ng, M.
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2018, 35 (04) : 4309 - 4317