《山东大学学报(理学版)》 ›› 2022, Vol. 57 ›› Issue (7): 73-84.doi: 10.6040/j.issn.1671-9352.0.2021.453
• • 上一篇
刘云,宋凯*,陈路遥,朱鹏俊
LIU Yun, SONG Kai*, CHEN Lu-yao, ZHU Peng-jun
摘要: 提出了一种均衡评估算法,通过在区块链中消除无线传感器网络中的恶意节点来增强信标节点之间的信任关系。首先将传感器节点信息打包生成区块,按照节点编号顺序生成区块链;接着在区块链中对每个信标节点进行基于行为、基于反馈和基于数据的信任值计算,将3个信任值加权得到每个信标节点的均衡信任值,并将均衡信任值广播给基站;最后对均衡信任值排序,把信任值较小的信标节点视为恶意节点,并将其从区块链中剔除。仿真结果显示,均衡评估算法在平均定位误差、检测精度和平均能耗等方面都有了很好的提升,同时保证了信任评估管理过程的安全性和可追溯性。
中图分类号:
[1] 邓玉静,王倩悦,尹荣荣,等.考虑级联失效的有向WSNs节点重要度评估模型[J]. 小型微型计算机系统, 2020, 41(1):111-116. DENG Yujing, WANG Qianyue, YIN Rongrong, et al. Evaluation model of node importance considering cascading failures in directed WSNs[J]. Journal of Chinese Computer Systems, 2020, 41(1):111-116. [2] 滕志军,庞宝贺,孙铭阳,等. 基于环境参数优化和时间信誉序列的恶意节点识别模型[J]. 西北工业大学学报, 2020, 38(3):634-642. TENG Zhijun, PANG Baohe, SUN Mingyang, et al. Model for malicious node recognition based on environmental parameter optimization and time reputation sequence[J]. Journal of Northwestern Polytechnical University, 2020, 38(3):634-642. [3] 周文雄,林穗. 无线传感网络恶意节点识别算法[J]. 计算机系统应用, 2020, 29(2):175-180. ZHOU Wenxiong, LIN Sui. Malicious node recognition algorithm in wireless sensor networks[J]. Computer Systems & Applications, 2020,29(2):175-180. [4] 夏伟. 基于传感器的无线网络恶意节点检测研究[J]. 西安文理学院学报(自然科学版), 2020, 23(4):41-46. XIA Wei. Research on sensor-based malicious node detection in wireless networks[J]. Journal of Xi an University(Natural Science Edition), 2020,23(4):41-46. [5] WEI She, LIU Qi, ZHAO Tian, et al. Blockchain trust model for malicious node detection in wireless sensor networks[J]. IEEE Access, 2019, 7:38947-38956. [6] TIAN Y L, WANG Z, XIONG J B, et al. A blockchain-based secure key management scheme with trustworthiness in DWSNs[J]. IEEE Transactions on Industrial Informatics, 2020, 16(9):6193-6202. [7] WU D, ANSARI N. A Trust-evaluation-enhanced blockchain-secured industrial IoT system[J]. IEEE Internet of Things Journal, 2021, 8(7):5510-5517. [8] WANG G, LU S W, YU F, et al. A method to improve the security of information diffusion in complex networks——node trust-value management mechanism[J]. IEEE Access, 2019, 7:138175-138191. [9] 周远林,陶洋,李正阳,等. 基于双簇头的无线传感器网络反馈信任模型[J]. 计算机工程, 2021, 47(3):174-182. ZHOU Yuanlin, TAO Yang, LI Zhengyang, et al. Double cluster head-based feedback trust model for wireless sensor network[J]. Computer Engineering, 2021, 47(3):174-182. [10] YU J Y, LEE E, OH S, et al. A survey on security requirements for WSNs: focusing on the characteristics related to security[J]. IEEE Access, 2020, 8:45304-45324. [11] ADERIBOLE A, ALJARWAN A, UR REHMAN M H, et al. Blockchain technology for smart grids: decentralized NIST conceptual model[J]. IEEE Access, 2020, 8:43177-43190. [12] 于戈,聂铁铮,李晓华,等. 区块链系统中的分布式数据管理技术:挑战与展望[J]. 计算机学报, 2021, 44(1):28-53. YU Ge, NIE Tiezheng, LI Xiaohua, et al. The challenge and prospect of distributed data management techniques in blockchain systems[J]. Chinese Journal of Computers, 2021, 44(1):28-53. [13] KIM T, GOYAT R, RAI M K, et al. A novel trust evaluation process for secure localization using a decentralized blockchain in wireless sensor networks[J]. IEEE Access, 2019, 7:184133-184144. [14] LIANG J B, ZHANG M, LEUNG V C M. A reliable trust computing mechanism based on multisource feedback and fog computing in social sensor cloud[J]. IEEE Internet of Things Journal, 2020, 7(6):5481-5490. [15] YAN X Z, LUO Q H, YANG Y P, et al. ITL-MEPOSA: improved trilateration localization with minimum uncertainty propagation and optimized selection of anchor nodes for wireless sensor networks[J]. IEEE Access, 2019,(7):53136-53146. |
[1] | 赵峰, 徐秀. 基于迭代双通信半径的传感器网络DV-Hop算法[J]. 山东大学学报(理学版), 2015, 50(07): 31-37. |
|