XU Jiu-qiang, ZHOU Yang-yang, WANG Jin-fa, ZHAO Hai. Anomaly Detection of Network Traffic Based on Flow Time Influence Domain[J]. Journal of Northeastern University Natural Science, 2019, 40(1): 26-31.
[1]程艳云,张守超,杨杨.基于大数据的时间序列异常点检测研究[J].计算机技术与发展,2016,26(5):139-144.(Cheng Yan-yun,Zhang Shou-chao,Yang Yang.Research on time series outlier detection based on big data.[J].Computer Technology and Development,2016,26(5):139-144.) [2]赵海,张娅,何璇,等.基于时空影响域的地震网络动力学演化特征分析[J].东北大学学报(自然科学版),2015,36(9):1232-1236.(Zhao Hai,Zhang Ya,He Xuan,et al.Dynamic evolution analysis of earthquake network based on the time-space influence domain[J].Journal of Northeastern University(Natural Science),2015,36(9):1232-1236.) [3]贺涛.基于网络数据流依赖关系的拟阵构造[D].上海:复旦大学,2009.(He Tao.Matroid contruction based on data streams dependent relationship in network[D].Shanghai:Fudan University,2009.) [4]程光,龚俭,丁伟.基于抽样测量的高速网络实时异常检测模型[J].软件学报,2003,14(3):594-599.(Cheng Guang,Gong Jian,Ding Wei.A real-time anomaly detection model based on sampling measurement in a high-speed network[J].Journal of Software,2003,14(3):594-599.) [5]Grill M,Stiborek J,Zunino A.An empirical comparison of botnet detection methods[J].Computers & Security,2014,45:100-123. [6]Akoglu L,Tong H,Koutra D.Graph based anomaly detection and description:a survey[J].Data Mining & Knowledge Discovery,2014,29(3):626-688. [7]Oz L E,Eilertson E,Lazarevic A,et al.MINDS-minnesota intrusion detection system[J].Cd Technology,2007,31(5):151-153. [8]Ahmed M,Mahmood A N,Hu J.A survey of network anomaly detection techniques[J].Journal of Network & Computer Applications,2016,60:19-31. [9]Sridharan N A,Ye T,Bhattacharyya N S.Connectionless port scan detection on the backbone[C]// IEEE International Performance Computing and Communications Conference.Phoenix,2006:567-576. [10]Tavallaee M,Stakhanova N,Ghorbani A A.Toward credible evaluation of anomaly-based intrusion-detection methods[J].IEEE Transactions on Systems Man & Cybernetics:Part C,2010,40(5):516-524. [11]Xu K,Zhang Z L,Bhattacharyya S.Profiling internet backbone traffic:behavior models and applications[J].ACM SIGCOMM Computer Communication Review,2005,35(4):169-180. [12]Barbara D,Wu N,Jajodia S.Detecting novel network intrusions using bayes[C]// Siam Conference on Data Mining.Philadelphia,2001:308-317. [13]Sengar H,Wang X,Wang H,et al.Online detection of network traffic anomalies using behavioral distance[C]// International Workshop on Quality of Service.Charleston:IEEE,2009:1-9. [14]Hua L,Joe H.Strength of tail dependence based on conditional tail expectation[J].Journal of Multivariate Analysis, 2014,123(1):143-159.(上接第5页) [13]Hesse W,Moller E,Arnold M,et al.The use of time-variant EEG Granger causality for inspecting directed interdependencies of neural assemblies [J].Journal of Neuroscience Methods,2003,124(1):27-44. [14]Afshari S,Jalili M.Directed functional networks in alzheimer’s disease:disruption of Glabal and local connectivity measuers [J].IEEE Journal of Biomedical and Health Informatics,2016,21(4):949-955. [15]Rubinov M,Sporns O.Complex network measures of brain connectivity:uses and interpretations [J].NeuroImage,2009,52(3):1059-1069. [16]Huang D,Ren A,Shang J,et al.Combining partial directed coherence and graph theory to analyse effective brain networks of different mental tasks [J]. Frontiers in Human Neuroscience,2016,10(5):1-11. [17]黄璐,王宏.基于约束独立分量分析的脑电特征提取[J].东北大学学报(自然科学版),2014,35(3):419-423.(Huang Lu,Wang Hong.EEG feature extraction based on constrained ICA[J].Journal of Northeastern University(Natural Science),2014,35(3):419-423.)