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
  • [1] RETRACTION: IoT individual privacy features analysis based on convolutional neural network (Retraction of Vol 57, Pg 126, 2019)
    Xi, Meng
    Lingyu, Nie
    Jiapeng, Song
    COGNITIVE SYSTEMS RESEARCH, 2024, 85
  • [2] A privacy protection method for IoT nodes based on convolutional neural network
    Han Y.
    Sun D.
    Li Y.
    International Journal of Reasoning-based Intelligent Systems, 2024, 16 (01) : 16 - 25
  • [3] A security and privacy preserving approach based on social IoT and classification using DenseNet convolutional neural network
    Maniveena, C.
    Kalaiselvi, R.
    AUTOMATIKA, 2024, 65 (01) : 333 - 342
  • [4] A security and privacy preserving approach based on social IoT evolving encoding using convolutional neural network
    Maniveena, C.
    Kalaiselvi, R.
    AUTOMATIKA, 2024, 65 (01) : 323 - 332
  • [5] Analysis and Recognition of Clinical Features of Diabetes Based on Convolutional Neural Network
    Wang, Rui
    Li, Ping
    Yang, Zhengfei
    COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE, 2022, 2022
  • [6] Cow Individual Identification Based on Convolutional Neural Network
    Lit, Zhangyong
    Ge, Chao
    Shen, Siwan
    Li, Xinwei
    2018 INTERNATIONAL CONFERENCE ON ALGORITHMS, COMPUTING AND ARTIFICIAL INTELLIGENCE (ACAI 2018), 2018,
  • [7] Privacy-aware quantum convolutional neural network for blockchain-based IoT health care data
    Jagdale, Balaso
    Sugave, Shounak Rushikesh
    Kulkarni, Yogesh R.
    Gutte, Vitthal
    INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS, 2024, 18 (02): : 1337 - 1354
  • [8] Privacy-CNH: A Framework to Detect Photo Privacy with Convolutional Neural Network Using Hierarchical Features
    Lam Tran
    Kong, Deguang
    Jin, Hongxia
    Liu, Ji
    THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2016, : 1317 - 1323
  • [9] Security and Privacy of Cloud- and IoT-Based Medical Image Diagnosis Using Fuzzy Convolutional Neural Network
    Deepika, J.
    Rajan, C.
    Senthil, T.
    COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2021, 2021
  • [10] Data Privacy Protection Model Based on Graph Convolutional Neural Network
    Gu, Tao
    Yang, Lin
    Wang, Hua
    MOBILE NETWORKS & APPLICATIONS, 2023,
12345