Crowdsensed Data-oriented Distributed and Secure Spatial Query Scheme

被引:0
作者
Li, Yuxi [1 ]
Zhou, Fucai [2 ]
Chen, Jingjing [1 ]
Ji, Dong [3 ]
机构
[1] Northeastern Univ, Sch Comp Sci & Engn, Shenyang, Peoples R China
[2] Northeastern Univ, Software Coll, Shenyang, Peoples R China
[3] Northeastern Univ, Natl Frontiers Sci Ctr Ind Intelligence & Syst Op, Shenyang, Peoples R China
来源
2023 IEEE 22ND INTERNATIONAL CONFERENCE ON TRUST, SECURITY AND PRIVACY IN COMPUTING AND COMMUNICATIONS, TRUSTCOM, BIGDATASE, CSE, EUC, ISCI 2023 | 2024年
关键词
mobile crowdsensing; secure data sharing; spatial queries; query pattern; access control; LOCATION-PRIVACY;
D O I
10.1109/TrustCom60117.2023.00130
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Focusing on the privacy concerns and leakage abuse of sensory data collection in mobile crowdsensing (MCS) environment, we propose a crowdsensed data-oriented distributed and secure spatial query scheme while ensuring data privacy as long as query patterns. To cater to the demands of real-world MCS workloads, we designed a distributed multi-layer architecture and leveraged distributed hash functions(DHT) and broadcast encryption(BE) to achieve load-balancing and enforce access control. Our scheme incorporates a recently developed cryptographic tool-function secret sharing (FSS) to safeguard the query pattern and sensory data from potential compromises at the server layer. The analysis demonstrates that our scheme achieves affordable query complexity while satisfying adaptive L-semantic security. Encouraging experimental results substantiate the efficacy of our scheme, the growth rates of query cost diminishes as the number of records and participants increases. These findings emphasize the suitability of our scheme for crowdsensing applications with fine-grained access control requirements and establish it as an efficient cryptographic tool that holds promise for diverse MCS applications.
引用
收藏
页码:912 / 919
页数:8
相关论文
共 25 条
  • [11] Data-Oriented Mobile Crowdsensing: A Comprehensive Survey
    Liu, Yutong
    Kong, Linghe
    Chen, Guihai
    [J]. IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2019, 21 (03): : 2849 - 2885
  • [12] Oblix: An Efficient Oblivious Search Index
    Mishra, Pratyush
    Poddar, Rishabh
    Chen, Jerry
    Chiesa, Alessandro
    Popa, Raluca Ada
    [J]. 2018 IEEE SYMPOSIUM ON SECURITY AND PRIVACY (SP), 2018, : 279 - 296
  • [13] Fast and Flexible Conversion of Geohash Codes to and from Latitude/Longitude Coordinates
    Moussalli, Roger
    Srivatsa, Mudhakar
    Asaad, Sameh
    [J]. 2015 IEEE 23RD ANNUAL INTERNATIONAL SYMPOSIUM ON FIELD-PROGRAMMABLE CUSTOM COMPUTING MACHINES (FCCM), 2015, : 179 - 186
  • [14] A Real-Time Data Collection Mechanism With Trajectory Privacy in Mobile Crowd-Sensing
    Niu, Xin
    Huang, Hongyu
    Li, Yantao
    [J]. IEEE COMMUNICATIONS LETTERS, 2020, 24 (10) : 2114 - 2118
  • [15] Ren L., 2013, 40 ANN INT S COMPUTE, P571, DOI DOI 10.1145/2485922.2485971
  • [16] Chord: A scalable peer-to-peer lookup protocol for Internet applications
    Stoica, I
    Morris, R
    Liben-Nowell, D
    Karger, DR
    Kaashoek, MF
    Dabek, F
    Balakrishnan, H
    [J]. IEEE-ACM TRANSACTIONS ON NETWORKING, 2003, 11 (01) : 17 - 32
  • [17] A Signature Scheme with Unlinkable-yet-Accountable Pseudonymity for Privacy-Preserving Crowdsensing
    Sucasas, Victor
    Mantas, Georgios
    Bastos, Joaquim
    Damiao, Francisco
    Rodriguez, Jonathan
    [J]. IEEE TRANSACTIONS ON MOBILE COMPUTING, 2020, 19 (04) : 752 - 768
  • [18] The OpenSSL Project, 2015, OpenSSL: The Open Source Toolkit for SSL/TLS
  • [19] A Comparative Study on Human Activity Recognition Using Inertial Sensors in a Smartphone
    Wang, Aiguo
    Chen, Guilin
    Yang, Jing
    Zhao, Shenghui
    Chang, Chih-Yung
    [J]. IEEE SENSORS JOURNAL, 2016, 16 (11) : 4566 - 4578
  • [20] Location protection method for mobile crowd sensing based on local differential privacy preference
    Wang, Jian
    Wang, Yanli
    Zhao, Guosheng
    Zhao, Zhongnan
    [J]. PEER-TO-PEER NETWORKING AND APPLICATIONS, 2019, 12 (05) : 1097 - 1109