【摘要】 为了剔除区块链模块内的冗余性及攻击性流量信息,使用户拥有更多使用空间,提出了一种可扩展区块链模块的异常流量检测方法。重构区块链模块相空间,得到流量的向量轨迹,根据统计量检测区块链模块的最大流,进而得到整体模块内的流量统计值;采集模块端口的输入与输出流量含有的统计特征,利用指数加权移动平均法构建参数模拟模型,依据流量的统计特征对应完成对区块链模块的异常流量检测。仿真结果表明,所提方法能够对异常流量更为快速地检测,检测精度高,检测性能优越。更多还原

【Abstract】 In order to eliminate the redundancy and offensive traffic information in blockchain modules, a method to detect abnormal traffic of extensible blockchain modules was proposed. Firstly, we reconstructed the phase space of blockchain module to get the vector trajectory. Secondly, we detected the maximum flow of blockchain module by the statistics, and then we obtained the value of traffic statistics in the overall module. Moreover, we collected the statistical features of the input and output flow of module port. Meanwhile, we used the method of exponential weighted moving average to build a model of parameter simulation. Finally, we completed the abnormal traffic detection for blockchain modules according to the statistical characteristics. Simulation results prove that the proposed method can detect abnormal traffic more quickly, with high accuracy and excellent performance.更多还原