teo-sl / DPLAN_pytorchLinks
This repository contains an implementation of an anomaly detection method called DPLAN, which is based on the reinforcement learning framework. The method is described in the paper "Toward Deep Supervised Anomaly Detection: Reinforcement Learning from Partially Labeled Anomaly Data" by Pang et al.
☆12Updated last year
Alternatives and similar repositories for DPLAN_pytorch
Users that are interested in DPLAN_pytorch are comparing it to the libraries listed below
Sorting:
- Paper Implementation☆27Updated last year
- Using RL for anomaly detection in NSL-KDD☆122Updated 2 years ago
- ☆16Updated 2 years ago
- A tool for data preprocess on iTrust SWaT dataset.☆55Updated 3 years ago
- Reinforcement Learning-Based Model Selection for Anomaly Detection (RLMSAD)☆30Updated 3 years ago
- Code for the paper: "Supervised contrastive learning over prototype-label embeddings for network intrusion detection"☆15Updated 4 years ago
- ☆20Updated 8 months ago
- Code support as a published paper!☆61Updated last year
- ☆21Updated 5 years ago
- ☆11Updated last year
- Intrusion Detection System (Classifier) Using CIC IDS 2017 Datasets☆14Updated 4 years ago
- Repository for IEEE CCNC'21 paper titled "Edge-Detect: Edge-centric Network Intrusion Detection using Deep Neural Network".☆47Updated 2 years ago
- Deep learning-based outlier/anomaly detection☆547Updated 2 months ago
- [VLDB'22] Anomaly Detection using Transformers, self-conditioning and adversarial training.☆622Updated last year
- Cyber-attack classification in the network traffic database using NSL-KDD dataset☆27Updated 5 years ago
- Implement a VAE to learn a reduced state space representation from the NSL-KDD dataset, capturing essential features of normal network t…☆13Updated last year
- A GAN-based model focused on anomaly detection in discrete dataset☆26Updated 5 years ago
- ☆19Updated 3 years ago
- NEGSC☆41Updated last year
- Synthesis of Adversarial DDos Attacks Using Tabular Generative Adversarial Networks☆10Updated 2 years ago
- CANET: An Effective CNN-Attention Model for Network Intrusion Detection☆38Updated 2 years ago
- Here, we use RNN to deal with the network intrusion problem. The UNSW-NB15 dataset is used.☆74Updated 4 years ago
- Intrusion Detection System using Deep Reinforcement Learning and Generative Adversarial Networks☆47Updated last year
- Implementation of 2 VAE architectures with LSTM and GRU for anomaly detection on sequential data☆24Updated 3 years ago
- Public datasets for time series anomaly detection☆131Updated 3 weeks ago
- Learning Graph Structures with Transformer for Multivariate Time Series Anomaly Detection in IoT☆145Updated 3 years ago
- ADRepository: Real-world anomaly detection datasets, including tabular data (categorical and numerical data), time series data, graph dat…☆415Updated 2 weeks ago
- A study on Deep Learning and Graph Neural Network for Intrusion Detection and Prevention (CNN, VAE, GNN,...)☆14Updated 2 years ago
- convGRU based autoencoder for unsupervised & spatial-temporal anomaly detection in computer network (PCAP) traffic.☆17Updated last year
- 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…☆46Updated 3 years ago