Smart Grid and Innovative Frontiers in Telecommunications. 5th EAI International Conference, SmartGIFT 2020, Chicago, USA, December 12, 2020, Proceedings

Research Article

A Resource Consumption Attack Identification Method Based on Data Fusion

Download
133 downloads
  • @INPROCEEDINGS{10.1007/978-3-030-73562-3_11,
        author={Libin Jiao and Yonghua Huo and Ningling Ge and Zhongdi Ge and Yang Yang},
        title={A Resource Consumption Attack Identification Method Based on Data Fusion},
        proceedings={Smart Grid and Innovative Frontiers in Telecommunications. 5th EAI International Conference, SmartGIFT 2020, Chicago, USA, December 12, 2020, Proceedings},
        proceedings_a={SMARTGIFT},
        year={2021},
        month={7},
        keywords={Resource consumption attack Correlation analysis Data fusion D-S evidence theory},
        doi={10.1007/978-3-030-73562-3_11}
    }
    
  • Libin Jiao
    Yonghua Huo
    Ningling Ge
    Zhongdi Ge
    Yang Yang
    Year: 2021
    A Resource Consumption Attack Identification Method Based on Data Fusion
    SMARTGIFT
    Springer
    DOI: 10.1007/978-3-030-73562-3_11
Libin Jiao1, Yonghua Huo1, Ningling Ge2, Zhongdi Ge3, Yang Yang3
  • 1: The 54th Research Institute of CETC
  • 2: Agricultural Bank of China
  • 3: Beijing University of Posts and Telecommunications

Abstract

Data fusion can make use of information from different sources or different representations to describe the target more accurately, which has important research significance. Aiming at the network-running node may be attacked or there is measurement error, this paper comprehensively utilizes the information of each node, and proposes a resource consumption attack identification method based on node multi-dimensional data fusion. First, construct a correlation matrix between nodes, identify normal nodes and possible abnormal nodes, and assign different weights to each node. Then, calculating the support of the node's system attributes for the attack type, and adopting the D-S evidence theory to effectively identify the network attack. The simulations demonstrate the effectiveness and certain advantages of the proposed algorithm.