IoT individual privacy features analysis based on convolutional neural network

被引：6
|
作者：
Meng Xi [1 ]
Nie Lingyu [1 ]
Song Jiapeng [1 ]
机构：
[1] Chinese Peoples Publ Secur Univ, Sch Invest & Counter Terrorism, Beijing 100038, Peoples R China
来源：
COGNITIVE SYSTEMS RESEARCH | 2019年 / 57卷
关键词：
Convolutional neural network; Individual privacy; Global restriction; Protection algorithm; CLASSIFICATION; POLYMERS;
D O I：
10.1016/j.cogsys.2018.09.031
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In terms of the evaluation problems about individual privacy defense situation of cyberspace, an evaluation method for individual privacy security defense situation based on convolutional neural network is proposed in this thesis; firstly, the state of situation factor at different times in the individual privacy defense system is subject to fuzzy and probabilistic processing based on Bayesian algorithm, to build up situation awareness and situation estimation model and then input the initial condition probability, state transition probability and observation data into the model; secondly, the convolutional neural network is introduced to recognize and evaluate the Bayesian algorithm model mentioned above, improving the accuracy of global restriction protection algorithm for individual privacy features; finally, simulation experiment is carried out to verify the performance advantages of modeling of the algorithm mentioned above. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码：126 / 130
页数：5
相关论文
共 50 条
  • [31] Network Attack Identification and Analysis Based on Graph Convolutional Neural Network
    Wang, Xingyu
    Wenkun
    Zhang, Yingdan
    2023 IEEE 22ND INTERNATIONAL CONFERENCE ON TRUST, SECURITY AND PRIVACY IN COMPUTING AND COMMUNICATIONS, TRUSTCOM, BIGDATASE, CSE, EUC, ISCI 2023, 2024, : 1443 - 1448
  • [32] Smart IoT Network Based Convolutional Recurrent Neural Network With Element-Wise Prediction System
    Al-Jamali, Nadia Adnan Shiltagh
    Al-Raweshidy, Hamed S.
    IEEE ACCESS, 2021, 9 : 47864 - 47874
  • [33] An Efficient Federated Convolutional Neural Network Scheme with Differential Privacy
    Zhang, Dayin
    Chen, Xiaojun
    Shi, Jinqiao
    EMERGING INFORMATION SECURITY AND APPLICATIONS, EISA 2022, 2022, 1641 : 173 - 190
  • [34] A Scheme of Privacy-Preserving Convolutional Neural Network Prediction
    Ren Y.-L.
    Yu L.-Z.
    He G.
    Zhang X.-P.
    Guo Z.
    Jisuanji Xuebao/Chinese Journal of Computers, 2023, 46 (08): : 1606 - 1619
  • [35] Compact Convolutional Neural Network Accelerator for IoT Endpoint SoC
    Ge, Fen
    Wu, Ning
    Xiao, Hao
    Zhang, Yuanyuan
    Zhou, Fang
    ELECTRONICS, 2019, 8 (05)
  • [36] IoTNet: An Efficient and Accurate Convolutional Neural Network for IoT Devices
    Lawrence, Tom
    Zhang, Li
    SENSORS, 2019, 19 (24)
  • [37] Android Ransomware Analysis Using Convolutional Neural Network and Fuzzy Hashing Features
    Rodriguez-Bazan, Horacio
    Sidorov, Grigori
    Escamilla-Ambrosio, Ponciano Jorge
    IEEE ACCESS, 2023, 11 : 121724 - 121738
  • [38] An Image Mosaic Method Based on Convolutional Neural Network Semantic Features Extraction
    Zaifeng Shi
    Hui Li
    Qingjie Cao
    Huizheng Ren
    Boyu Fan
    Journal of Signal Processing Systems, 2020, 92 : 435 - 444
  • [39] Research on the extraction method of painting style features based on convolutional neural network
    Jiang, Hua
    Yang, Ting
    INTERNATIONAL JOURNAL OF ARTS AND TECHNOLOGY, 2022, 14 (01) : 40 - 55
  • [40] Task-Driven Dictionary Learning based on Convolutional Neural Network Features
    Tirer, Tom
    Giryes, Raja
    2018 26TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), 2018, : 1885 - 1889
12345