• 中国精品科技期刊
  • CCF推荐A类中文期刊
  • 计算领域高质量科技期刊T1类
Advanced Search
Ma Xingpo, Liang Junbin, Ma Wenpeng, Li Yin, Li Ran, Kui Xiaoyan. A Secure Top-k Query Processing Protocol for Two-Tiered Wireless Sensor Networks[J]. Journal of Computer Research and Development, 2018, 55(11): 2490-2500. DOI: 10.7544/issn1000-1239.2018.20170666
Citation: Ma Xingpo, Liang Junbin, Ma Wenpeng, Li Yin, Li Ran, Kui Xiaoyan. A Secure Top-k Query Processing Protocol for Two-Tiered Wireless Sensor Networks[J]. Journal of Computer Research and Development, 2018, 55(11): 2490-2500. DOI: 10.7544/issn1000-1239.2018.20170666

A Secure Top-k Query Processing Protocol for Two-Tiered Wireless Sensor Networks

More Information
  • Published Date: October 31, 2018
  • Because of the advantages of strong robustness and good scalability, TWSNs (two-tiered wireless sensor networks), which are known as parts of the IoT (Internet of things) observation systems, attract more and more attention. However, many security problems have not yet been well solved in TWSNs. In hostile environments, the adversaries are prone to illegally obtain the information stored on the master nodes, which are known as the key nodes of TWSNs, and even destroy the integrity of the query results returned to Sink node by capturing the master nodes and making them malicious. In this paper, we focus on the problem of privacy-and-integrity preservation for Top-k queries in TWSNs and propose a secure query-processing protocol named VPP (verifiable privacy-and-integrity preservation). Based on the OPES (order preserving encryption scheme), the SC (symmetric ciphering) and the weight binding techniques, VPP achieves privacy-and-integrity preservation for Top-k queries by specifying the data preprocessing mechanism at the sensor nodes, the Top-k query-processing mechanism at the storage nodes, and the integrity-validating method at Sink node. Both theoretic analysis and simulation results show that VPP outperforms the state-of-the-art scheme on not only the security but also the energy efficiency of Top-k query processing in TWSNs with reasonable computation complexity.
  • Related Articles

    [1]Lu Shaoshuai, Chen Long, Lu Guangyue, Guan Ziyu, Xie Fei. Weakly-Supervised Contrastive Learning Framework for Few-Shot Sentiment Classification Tasks[J]. Journal of Computer Research and Development, 2022, 59(9): 2003-2014. DOI: 10.7544/issn1000-1239.20210699
    [2]Jia Xibin, Jin Ya, Chen Juncheng. Domain Alignment Based on Multi-Viewpoint Domain-Shared Feature for Cross-Domain Sentiment Classification[J]. Journal of Computer Research and Development, 2018, 55(11): 2439-2451. DOI: 10.7544/issn1000-1239.2018.20170496
    [3]Chen Long, Guan Ziyu, He Jinhong, Peng Jinye. A Survey on Sentiment Classification[J]. Journal of Computer Research and Development, 2017, 54(6): 1150-1170. DOI: 10.7544/issn1000-1239.2017.20160807
    [4]Zhang Zhifei, Miao Duoqian, Nie Jianyun, Yue Xiaodong. Sentiment Uncertainty Measure and Classification of Negative Sentences[J]. Journal of Computer Research and Development, 2015, 52(8): 1806-1816. DOI: 10.7544/issn1000-1239.2015.20150253
    [5]Zhao Chuanjun, Wang Suge, Li Deyu, Li Xin. Cross-Domain Text Sentiment Classification Based on Grouping-AdaBoost Ensemble[J]. Journal of Computer Research and Development, 2015, 52(3): 629-638. DOI: 10.7544/issn1000-1239.2015.20140156
    [6]Hou Yongshuai, Zhang Yaoyun, Wang Xiaolong, Chen Qingcai, Wang Yuliang, and Hu Baotian. Recognition and Retrieval of Time-sensitive Question in Chinese QA System[J]. Journal of Computer Research and Development, 2013, 50(12): 2612-2620.
    [7]Li Suke and Jiang Yanbing. Semi-Supervised Sentiment Classification Based on Sentiment Feature Clustering[J]. Journal of Computer Research and Development, 2013, 50(12): 2570-2577.
    [8]Wu Qiong, Liu Yue, Shen Huawei, Zhang Jin, Xu Hongbo, and Cheng Xueqi. A Unified Framework for Cross-Domain Sentiment Classification[J]. Journal of Computer Research and Development, 2013, 50(8): 1683-1689.
    [9]Lin Zheng, Tan Songbo, Cheng Xueqi. Sentiment Classification Analysis Based on Extraction of Sentiment Key Sentence[J]. Journal of Computer Research and Development, 2012, 49(11): 2376-2382.
    [10]Hu Yi, Lu Ruzhan, Li Xuening, Duan Jianyong, ChenYuquan. Research on Language Modeling Based Sentiment Classification of Text[J]. Journal of Computer Research and Development, 2007, 44(9): 1469-1475.
  • Cited by

    Periodical cited type(8)

    1. 杨小东,周航,任宁宁,袁森,王彩芬. 支持多密文等值测试的无线体域网聚合签密方案. 计算机研究与发展. 2023(02): 341-350 . 本站查看
    2. 杨蒙蒙,江昆,温拓朴,陈会仙,黄晋,张浩,黄健强,唐雪薇,杨殿阁. 自动驾驶高精度地图众源更新技术现状与挑战. 中国公路学报. 2023(05): 244-259 .
    3. 王妍,白洪亮,蒋方正,张英伟. 露天矿无人驾驶运输关键技术研究. 现代矿业. 2023(10): 178-181 .
    4. 丁晓晖,曹素珍,窦凤鸽,马佳佳,王彩芬. 基于无证书聚合签名的导航信息更新方案. 计算机技术与发展. 2022(06): 112-119 .
    5. 杜田,李欣,赖成喆,郑东. 面向无人驾驶地图更新的安全信任管理方案. 计算机工程. 2022(06): 154-166 .
    6. 李月华. 基于自动驾驶众包地图更新技术方法. 北京测绘. 2022(05): 629-635 .
    7. 陈虹,侯宇婷,郭鹏飞,周沫,赵菊芳,肖成龙. 可公开验证的高效无证书聚合签密方案. 计算机工程. 2022(10): 146-157 .
    8. 陶永才,李哲,石磊,卫琳,杨淑博. 一种可信的车联网区块链数据共享模型. 小型微型计算机系统. 2021(10): 2131-2139 .

    Other cited types(5)

Catalog

    Article views (1026) PDF downloads (354) Cited by(13)

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return