yihanchen3 / Network-Anomaly-Traffic-Detection-and-Prediction-using-Spatio-Temporal-NetworksLinks
Purposed a network traffic classification and prediction model based on CNN, TCN and Attention mechanism.
☆22Updated 2 years ago
Alternatives and similar repositories for Network-Anomaly-Traffic-Detection-and-Prediction-using-Spatio-Temporal-Networks
Users that are interested in Network-Anomaly-Traffic-Detection-and-Prediction-using-Spatio-Temporal-Networks are comparing it to the libraries listed below
Sorting:
- the DL methods used are : DNN, CNN, LSTM, GRU, CNN-LSTM, CNN-GRU, CNN-BiLSTM, CNN-BiGRU, the dataset used is : imbalanced NSL-KDD (KDDTra…☆47Updated 3 years ago
- CANTransfer: Transfer learning based intrusion detection on a controller area network using convolutional LSTM network☆17Updated 5 years ago
- This is the source code of "Intrusion Detection of Industrial Internet-of-Things Based on Reconstructed Graph Neural Networks"☆12Updated last year
- A Deep Learning Based Intrusion Detection System for IIoT Networks☆12Updated last year
- ☆21Updated 5 years ago
- 异常检测算法☆20Updated 2 years ago
- convGRU based autoencoder for unsupervised & spatial-temporal anomaly detection in computer network (PCAP) traffic.☆17Updated last year
- Protocol-Based Deep Intrusion Detection for DoS and DDoS Attacks Using UNSW-NB15 and Bot-IoT Data-Sets☆23Updated 3 years ago
- 网络流量预测☆22Updated 2 years ago
- Replication of Jay Sinha's Efficient Deep CNN-BiLSTM model for network intrusion detection using NSL-KDD and UNSW-NB15 datasets to unders…☆15Updated last year
- CANET: An Effective CNN-Attention Model for Network Intrusion Detection☆37Updated 2 years ago
- MD,LSTM-AE,VAE-MAD-GAN☆31Updated 4 years ago
- Repository for the paper titled "Attention-based Bi-LSTM for Anomaly Detection on Time-Series Data"☆22Updated 4 years ago
- This study proposes a two- level classification technique for the anomaly detection-based IDS architecture for fog-edge sides. Targeted f…☆13Updated 3 years ago
- Code support as a published paper！☆67Updated last year
- ☆14Updated 4 years ago
- Implement a VAE to learn a reduced state space representation from the NSL-KDD dataset, capturing essential features of normal network t…☆14Updated last year
- This repository presents the implemetation of a highly optimized Deep Transfer Learning (DTL) and Genetic Algorithm (GA) based intrusion …☆22Updated 2 years ago
- Development of a transfer learning system for the detection of cyber-attacks in 5G and IoT networks. Transfer learning will improve the a…☆15Updated 3 years ago
- Anomaly based Instrusion Detection System using RNN-LSTMs. Datasets include NSL-KDD and UNSW-NB15.☆35Updated 5 years ago
- Implementation of 2 VAE architectures with LSTM and GRU for anomaly detection on sequential data☆24Updated 4 years ago
- CNN with attention and CNN_LSTM_attention(pytorch)☆18Updated 6 years ago
- Modern and future vehicles are complex cyber-physical sys-tems. The connection to their outside environment raises many securityproblems …☆19Updated 4 years ago
- A novel time series forecasting model, called CEEMDAN-TCN.☆11Updated 3 years ago
- Here, we use RNN to deal with the network intrusion problem. The UNSW-NB15 dataset is used.☆75Updated 5 years ago
- ☆26Updated 3 years ago
- A Graph Neural Network-based Intrusion Detection System☆29Updated last year
- We use attention model for intrusion detection. The idea of Hierarchical Attention Model for Intrusion Detection comes from the applicat…☆12Updated 5 years ago
- Improved Autoencoder-based Ensemble In-vehicle Intrusion Detection System☆13Updated 2 years ago
- Adaptive Hybrid Spatial-Temporal Graph Neural Network for Cellular Traffic Prediction☆26Updated 2 years ago