Anomaly detection with ensemble empirical mode decomposition and approximate entropy for quick user datagram protocol internet connection-based distributed Blockchain systems

【Author】 Cao, Yuanlong; Gu, Keyang; Wu, Junyi; Zou, Xiang; Tao, Lei; Huang, Xin; Jiang, Changgen

【Source】IET SOFTWARE

【影响因子】1.150

【Abstract】With the vigorous development of mobile Internet and Blockchain, the rapid and secure interaction of high-frequency data in the era of data explosion has gradually become an urgent need for people. Quick User Datagram Protocol Internet Connection Protocol (QUIC) can be perfectly integrated into the Blockchain due to its low latency and high security, providing a safe and reliable transmission service for the Blockchain system. However, QUIC-based distributed Blockchain systems are vulnerable to cyberattacks due to asymmetric encryption and timestamp, which seriously impacts security and fairness. Therefore, based on the self-similarity of QUIC network traffic, this study proposes an anomaly detection model for QUIC network traffic based on Ensemble Empirical Mode Decomposition and Approximate Entropy. The model obtains several intrinsic mode functions and a residual term by decomposing the network traffic, introducing Approximate Entropy to judge the complexity of each component, and using the Hurst parameter to determine the generation of abnormal traffic. Compared with traditional detection methods, the model can effectively overcome the problems of poor adaptive ability and low efficiency and has high accuracy, which can be used for attack detection and prevention of network nodes.

【Keywords】computer network security; data flow analysis; software reliability; transport protocols

【发表时间】

【收录时间】2023-03-05

【文献类型】实验仿真

【主题类别】

区块链技术-核心技术-区块传输