| ［1］ |
蹇诗婕，卢志刚，杜丹，等.网络入侵检测技术综述［J］.信息安全学报，2020，5（4）:96-122.
|
|
Jian Shi-jie, Lu Zhi-gang, Du Dan,et al. Overview of network intrusion detection technology［J］. Journal of Cyber Security,2020,5(4):96-122.
|
| ［2］ |
Gamage S,Samarabandu J.Deep learning methods in network intrusion detection:A survey and an objective comparison ［J］.Journal of Network and Computer Applications,2020,169:102767.
|
| ［3］ |
Salo F,Nassif A B,Essex A.Dimensionality reduction with IG-PCA and ensemble classifier for network intrusion detection ［J］.Computer Networks,2019,148:164-175.
|
| ［4］ |
An J,Cho S.Variational autoencoder based anomaly detection using reconstruction probability ［J］.Special Lecture on IE,2015,2 (1):1-18.
|
| ［5］ |
Zong B,Song Q,Min M R,et al.Deep autoencoding Gaussian mixture model for unsupervised anomaly detection ［C］∥Proc of International Conference on Learning Representations,2018:1-19.
|
| ［6］ |
Zhao Y,Hryniewicki M K.XGBOD:Improving supervised outlier detection with unsupervised representation learning ［C］∥Proc of 2018 International Joint Conference on Neural Networks,2018:1-8.
|
| ［7］ |
Ruff L, Vandermeulen R A, Grnitz N, et al.Deep semi- supervised anomaly detection ［J］.arXiv:1906.02694,2019.
|
| ［8］ |
Ruff L,Vandermeulen R,Grnitz N,et al.Deep one-class classification ［C］∥Proc of the 35th International Conference on Machine Learning,2018:4393-4402.
|
| ［9］ |
Pang G,Cao L,Chen L,et al.Learning representations of ultrahigh dimensional data for random distance-based outlier detection ［C］∥Proc of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining,2018:2041-2050.
|
| ［10］ |
Pang G,Shen C,van den Hengel A.Deep anomaly detection with deviation networks ［C］∥Proc of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining,2019:353-362.
|
| ［11］ |
Pang G S,Shen C H,Jin H D,et al.Deep weakly-supervised anomaly detection ［J］.arXiv:1910.13601,2019.
|
| ［12］ |
Zhou Y,Song X,Zhang Y,et al.Feature encoding with autoencoders for weakly supervised anomaly detection ［J］.IEEE Transactions on Neural Networks and Learning Systems,2021,33(6):2454-2465.
|
| ［13］ |
Grnitz N,Kloft M,Rieck K,et al.Toward supervised anomaly detection ［J］.Journal of Artificial Intelligence Research,2013,46:235-262.
|
| ［14］ |
Huang T,Chen P,Li R. A semi-supervised VAE based active anomaly detection framework in multivariate time series for online systems ［C］∥Proc of the ACM Web Confe- rence,2022:1797-1806.
|
| ［15］ |
Zha D,Lai K-H,Wan M,et al.Meta-AAD:Active anomaly detection with deep reinforcement learning ［C］∥Proc of 2020 IEEE International Conference on Data Mining,2020:771-780.
|
| ［16］ |
Pang G,van den Hengel A,Shen C,et al.Toward deep supervised anomaly detection:Reinforcement learning from partially labeled anomaly data ［C］∥Proc of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining,2021:1298-1308.
|
| ［17］ |
Tavallaee M,Bagheri E,Lu W,et al.A detailed analysis of the KDD CUP 99 data set ［C］∥Proc of 2009 IEEE Symposium on Computational Intelligence for Security and Defense Applications,2009:1-6.
|
| ［18］ |
Moustafa N,Slay J.UNSW-NB15:A comprehensive data set for network intrusion detection systems (UNSW-NB15 network data set) ［C］∥Proc of 2015 Military Communications and Information Systems Conference,2015:1-6.
|
| ［19］ |
Kim J,Shin Y,Choi E.An intrusion detection model based on a convolutional neural network ［J］.Journal of Multimedia Information System,2019,6(4):165-172.
|
| ［20］ |
Goldstein M, Dengel A. Histogram-based outlier score (HBOS):A fast unsupervised anomaly detection algorithm ［C］∥Proc of KI-2012:Poster and Demo Track,2012:1-5.
|
| ［21］ |
Liu F T,Ting K M,Zhou Z-H.Isolation-based anomaly detection ［J］.ACM Transactions on Knowledge Discovery from Data,2012,6(1):Article No.:3.
|
