yihanchen3 / Network-Anomaly-Traffic-Detection-and-Prediction-using-Spatio-Temporal-Networks
Purposed a network traffic classification and prediction model based on CNN, TCN and Attention mechanism.
☆20Updated last year
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
- 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…☆44Updated 2 years ago
- This is the source code of "Intrusion Detection of Industrial Internet-of-Things Based on Reconstructed Graph Neural Networks"☆11Updated last year
- CANTransfer: Transfer learning based intrusion detection on a controller area network using convolutional LSTM network☆12Updated 4 years ago
- 异常检测算法☆18Updated last year
- Protocol-Based Deep Intrusion Detection for DoS and DDoS Attacks Using UNSW-NB15 and Bot-IoT Data-Sets☆21Updated 2 years ago
- 网络流量预测☆19Updated 2 years ago
- Training an LSTM-based autoencoder to detect anomalies in the KDD99 network traffic dataset.☆14Updated 4 years ago
- This project aims to detect the anomalies in Web-Traffic using a C-LSTM architecture.☆24Updated 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 2 years ago
- Here, we use RNN to deal with the network intrusion problem. The UNSW-NB15 dataset is used.☆68Updated 4 years ago
- using 2d-cnn to classify network traffic☆20Updated 5 years ago
- CNN with attention and CNN_LSTM_attention(pytorch)☆18Updated 5 years ago
- Implementation of a multi-task model for encrypted network traffic classification based on transformer and 1D-CNN.☆31Updated last year
- A Deep Learning Based Intrusion Detection System for IIoT Networks☆10Updated 9 months ago
- The proposed hybrid IDS is tested on two public network datasets, the CSE-CIC-IDS2018 and the TON IoT datasets, representing internal and…☆13Updated 2 years ago
- 论文Encrypted Traffic Classification with One-dimensional Convolution Neural Networks的torch实现☆35Updated 2 years ago
- We use attention model for intrusion detection. The idea of Hierarchical Attention Model for Intrusion Detection comes from the applicat…☆12Updated 4 years ago
- NEGSC☆38Updated 10 months ago
- ⼀个有潜⼒的⽹络⼊侵检测算法，引⼊了乘法注意⼒机制将其融合到 CNN 的分类模型中，在KDD99和UNSM-NB15数据集进行模型的训练结果优于一般机器学习方法和CNN。A promising network intrusion detection algorithm is…☆10Updated last year
- Improving Transferability of Network Intrusion Detection in a Federated Learning Setup☆12Updated last year
- convGRU based autoencoder for unsupervised & spatial-temporal anomaly detection in computer network (PCAP) traffic.☆17Updated last year
- Intrusion Detection System using Deep Reinforcement Learning and Generative Adversarial Networks☆44Updated 7 months ago
- CANET: An Effective CNN-Attention Model for Network Intrusion Detection☆33Updated 2 years ago
- Anomaly based Instrusion Detection System using RNN-LSTMs. Datasets include NSL-KDD and UNSW-NB15.☆34Updated 4 years ago
- ☆21Updated 4 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 …☆14Updated 2 years ago
- This platform is designed and implemented for encrypted traffic classification using deep learning☆13Updated last year
- GAN / AUTOENCODER for network intrusion detection using NSL-KDD dataset: https://www.kaggle.com/datasets/hassan06/nslkdd☆17Updated last year
- Adaptive Hybrid Spatial-Temporal Graph Neural Network for Cellular Traffic Prediction☆23Updated last year
- Repository for the paper titled "Attention-based Bi-LSTM for Anomaly Detection on Time-Series Data"☆22Updated 4 years ago