In order to ensure the safe operation of the network and maintain a high-quality data storage environ-ment,this paper proposed a method of detecting anomalies of network wireless network information flow based on the chaos algorithm.Firstly,the types of information flow abnormalities were classified according to the abnormal factors in wireless networks.Then,a wireless network distribution model was built according to the characteristics of different types of abnormalities.Based on the model,the overlapping dimension and the relevant dimension of abnormal infor-mation flow were clustered to obtain the dimension data of the wireless network.Moreover,the attribute judgment of the clusters was carried out by the abnormal factor method.Meanwhile,the original data and parameter variables were initialized.The clustering category in the set was marked.Finally,the chaos immune clustering algorithm was achieved through different threshold values.Thus,we completed the abnormal detection of network information flow.Experiments show that the proposed method can accurately detect abnormal information flow with low communication overhead,thus ensuring the safety of the network environment.
关键词
混沌算法/无线网络/网络信息流异常/维度获取/聚类融合
Key words
Chaos algorithm/Wireless network/Abnormal network information flow/Dimension acquisition/Clustering fusion
维普
万方数据