Alternatives and similar repositories for ghost-iot-dataset

Users that are interested in ghost-iot-dataset are comparing it to the libraries listed below

• racsa-lab / Edge-Detect
  Repository for IEEE CCNC'21 paper titled "Edge-Detect: Edge-centric Network Intrusion Detection using Deep Neural Network".
  ☆46Updated last year
• zuluokonkwo / Encrypted-Network-Traffic-Classification-with-Higher-Order-Graph-Neural-Network
  code repository for the the paper "Encrypted Network Traffic Classification with Higher Order Graph Neural Network"
  ☆33Updated 10 months ago
• polvalls9 / Transfer-Learning-Based-Intrusion-Detection-in-5G-and-IoT-Networks
  Development of a transfer learning system for the detection of cyber-attacks in 5G and IoT networks. Transfer learning will improve the a…
  ☆13Updated 2 years ago
• joejoe233 / TrafficClassification
  using 2d-cnn to classify network traffic
  ☆20Updated 5 years ago
• ANRGUSC / correlation_aware_ddos_iot
  Correlation Aware DDoS Detection In IoT Systems
  ☆9Updated last year
• BNN-UPC / GNN-NIDS
  ☆48Updated 3 years ago
• tcbenchstack / tcbench
  tcbench is a Machine Learning and Deep Learning framework to train model from traffic packet time series or other input representations.
  ☆26Updated 5 months ago
• Mobile-Intelligence-Lab / ACID
  Source code for the paper: Adaptive Clustering-based Malicious Traffic Classification at the Network Edge (https://homepages.inf.ed.ac.uk…
  ☆34Updated 4 years ago
• XAIseries / LEXNet
  LEXNet: A Lightweight, Efficient and Explainable-by-Design Convolutional Neural Network for Internet Traffic Classification
  ☆14Updated last year
• ghosh64 / transferability
  Improving Transferability of Network Intrusion Detection in a Federated Learning Setup
  ☆12Updated last year
• niloofarbayat / NetworkClassification
  ☆58Updated 2 years ago
• harshilpatel1799 / IoT-Network-Intrusion-Detection-and-Classification-using-Explainable-XAI-Machine-Learning
  The continuing increase of Internet of Things (IoT) based networks have increased the need for Computer networks intrusion detection sys…
  ☆50Updated 4 years ago
• andreaventuri01 / Structural_attacks_GNN_NIDS
  Official repository for the paper "Problem space structural adversarial attacks for Network Intrusion Detection Systems based on Graph Ne…
  ☆12Updated 10 months ago
• cdogemaru / CPIP
  ☆16Updated 2 years ago
• xgr19 / SAM-for-Traffic-Classification
  Self-attentive deep learning method for online traffic classification and its interpretability (CN21 & NetAI20)
  ☆37Updated 11 months ago
• waimorris / E-GraphSAGE
  A PyTorch implementation of of E-GraphSAGE.
  ☆89Updated 2 years ago
• doriguzzi / flad-federated-learning-ddos
  Adaptive Federated Learning Approach to DDoS attack detection
  ☆48Updated 6 months ago
• renj-xu / NEGSC
  NEGSC
  ☆38Updated last year
• SecTeamPolaris / ProGraph
  ☆15Updated last year
• Nir-J / ML-Projects
  Basic Machine learning projects and assignments done by me.
  ☆32Updated 4 years ago
• pfreitasaf / FIDGAN
  ☆21Updated 4 years ago
• manojkumar-github / Intrusion-Detection-System-for-IoT-networks-using-Gated-Recurrent-Neural-Networks-GRU
  An Intelligent Intrusion Detection System for IoT networks using Gated Recurrent Neural Networks (GRU) : A Deep Learning Approach
  ☆33Updated 6 years ago
• tsinghua-fib-lab / NetworkTrafficGeneration
  ☆19Updated 3 years ago
• Akrusher / Fs-net
  FS-Net: A Flow Sequence Network For Encrypted Traffic Classification
  ☆44Updated 4 years ago
• Rajlaxmi04 / Network-Traffic-Anomaly-Detection-using-PCA-and-BiGAN
  Anomaly Detection using PCA and BiGAN
  ☆13Updated 4 years ago
• meryemJanatiIdrissi / Fed-ANIDS
  ☆9Updated 2 years ago
• shrezaei / Semi-supervised-Learning-QUIC-
  Implementation of "How to Achieve High Classification Accuracy with Just a Few Labels: A Semi-supervised Approach Using Sampled Packets"
  ☆33Updated 6 years ago
• cx0113 / fine-grained-unknown-attack-detection
  ☆18Updated 4 years ago
• waimorris / Anomal-E
  A PyTorch implementation of of Anomal-E.
  ☆35Updated 2 years ago
• FlamingJay / Time-related-Intrusion-Detection-Model-based-on-Recurrent-Neural-Network
  Here, we use RNN to deal with the network intrusion problem. The UNSW-NB15 dataset is used.
  ☆70Updated 4 years ago