Privacy-Preserving Adaptive Multi-Channel Communications Under Timing Constraints

被引:7
|
作者
Gai, Keke [1 ]
Qiu, Meikang [1 ,2 ]
Zhao, Hui [3 ]
Dai, Wenyun [1 ]
机构
[1] Pace Univ, Dept Comp Sci, New York, NY 10038 USA
[2] Shenzhen Univ, Coll Comp Sci, Shenzhen, Peoples R China
[3] Henan Univ, Software Sch, Kaifeng 475000, Henan, Peoples R China
关键词
Privacy protection; multi-channel communication; timing constraint; big data; smart computing;
D O I
10.1109/SmartCloud.2016.50
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Currently, privacy leakage has become a great concern when a web-based application is applied. The threats deriving from communications are generally caused by implementing lower-level security protocols. However, using a higher-level privacy protection approach is often restricted by the efficiency requirements, since an enhanced security level needs a longer execution time than the approach offering a lower-level privacy protection. This work focuses on this issue and proposes a new approach that provides an adaptive multi-channel communications solution. The proposed approach is called Dynamic Multi-Channel Communications (DMC2) model, which is designed to dynamically determine the transport layer protocols in terms of the timing constraints. We consider four contemporary deployed protocol types the optional channels and our method can produce optimal solutions to maximizing the privacy level. Our experimental evaluations have examined the performance of DMC2, which demonstrates its privacy protection capability and the adaptability.
引用
收藏
页码:190 / 195
页数:6
相关论文
共 50 条
  • [1] Thora: Atomic and Privacy-Preserving Multi-Channel Updates
    Aumayr, Lukas
    Abbaszadeh, Kasra
    Maffei, Matteo
    PROCEEDINGS OF THE 2022 ACM SIGSAC CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY, CCS 2022, 2022, : 165 - 178
  • [2] Privacy-preserving multi-channel communication in Edge-of-Things
    Gai, Keke
    Qiu, Meikang
    Xiong, Zenggang
    Liu, Meiqin
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2018, 85 : 190 - 200
  • [3] Privacy-Functionality Trade-Off: A Privacy-Preserving Multi-Channel Smart Metering System
    Zhang, Xiao-Yu
    Kuenzel, Stefanie
    Cordoba-Pachon, Jose-Rodrigo
    Watkins, Chris
    ENERGIES, 2020, 13 (12)
  • [4] Privacy-Preserving Distributed Cooperative Spectrum Sensing in Multi-Channel Cognitive Radio MANETs
    Kasiri, Behzad
    Lambadaris, Ioannis
    Yu, Fei Richard
    Tang, Helen
    2015 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2015, : 7316 - 7321
  • [5] Privacy-Preserving Location Publishing under Road-Network Constraints
    Lin, Dan
    Gurung, Sashi
    Jiang, Wei
    Hurson, Ali
    DATABASE SYSTEMS FOR ADVANCED APPLICATIONS, PT II, PROCEEDINGS, 2010, 5982 : 17 - 31
  • [6] Learning Privacy-Preserving Channel Charts
    Agostini, Patrick
    Utkovski, Zoran
    Bjelakovic, Igor
    Stanczak, Slawomir
    FIFTY-SEVENTH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, IEEECONF, 2023, : 1654 - 1660
  • [7] Secure and privacy-preserving, timed vehicular communications
    Burmester, Mike
    Magkos, Emmanouil
    Chrissikopoulos, Vassilis
    INTERNATIONAL JOURNAL OF AD HOC AND UBIQUITOUS COMPUTING, 2012, 10 (04) : 219 - 229
  • [8] Privacy-Preserving Adaptive Resilient Consensus for Multi-Agent Systems under Cyber Attacks
    Ying, Chenduo
    Zheng, Ning
    Wu, Yiming
    Xu, Ming
    Zhang, Wen-An
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2024, 20 (02) : 1630 - 1640
  • [9] Adaptive privacy-preserving federated learning
    Liu, Xiaoyuan
    Li, Hongwei
    Xu, Guowen
    Lu, Rongxing
    He, Miao
    PEER-TO-PEER NETWORKING AND APPLICATIONS, 2020, 13 (06) : 2356 - 2366
  • [10] Adaptive privacy-preserving federated learning
    Xiaoyuan Liu
    Hongwei Li
    Guowen Xu
    Rongxing Lu
    Miao He
    Peer-to-Peer Networking and Applications, 2020, 13 : 2356 - 2366