gmgm123

gmgm123's Stars

• vinayakumarr/Network-Intrusion-Detection

  Network Intrusion Detection KDDCup '99', NSL-KDD and UNSW-NB15

  Language:Python650235

• Battlingboy/AE-IDS

  Network Intrusion Detection System(Abnormal Detection)

  Language:Python116

• CecileKafrouni/IntrusionDetection

  Language:Jupyter Notebook1

• drissgddm/ids-ml

  WIP/An Online Intrusion Detection System powered by a Machine Learning algorithm

  Language:Jupyter Notebook2

• geneura-papers/2015_honey

  Paper on the detection of intrusions

  Language:TeX1

• c2dc/AB-TRAP

  This is a five-step framework for the development of intrusion detection systems (IDS) using machine learning (ML) considering model realization, and performance evaluation.

  Language:Jupyter Notebook448

• Mickalu/detection_intrusion_VANET_network_deep_learning_machine_learning

  data treatment and implement of deep learning and machine learning for find intrusion.

  Language:Jupyter Notebook52

• N-Kishore-Kumar/Intrusion-Detection-System-using-ML-Algorithms

  Language:Python1

• wolfpython/nids

  基于网络的入侵检测系统

  Language:C5925

• xander-wang/logvision

  分布式实时日志分析与入侵检测系统

  Language:JavaScript19947

• CN-TU/adversarial-recurrent-ids

  Contact: Alexander Hartl, Maximilian Bachl, Fares Meghdouri. Explainability methods and Adversarial Robustness metrics for RNNs for Intrusion Detection Systems. Also contains code for "SparseIDS: Learning Packet Sampling with Reinforcement Learning" (branch "rl").

  Language:TeX1511

• soroushjavdan/SyntheticMinorityOverSamplingTechnique-SMOTE

  SMOTE is an algorithm that could be use for creating artificial sample from existing dataset

  Language:Python7

• adritor7/SMOTE-and-Tomek-Links-in-Spark

  Language:Scala81

• sartz18/Intrusion-Detection-Ensemble-Learning-and-Packet-Sniffer

  •Intrusion detection system that is able to classify a malicious packet into one of intrusion attack classes based upon its attributes. •Aiming to use a number of classifying algorithms like random forests, decision tree will be used and bagged together. •Used web sniffer to analyze real time Internet traffic as an extension.

  Language:Jupyter Notebook11

• dhelmr/bachelor-thesis

  Comparing Anomaly-Based Network Intrusion Detection Approaches Under Practical Aspects

  Language:Python10

• adityaiiith/Intrusion-Detection-System-IDS-

  An Intrusion Detection System based on Machine Learning Algorithms.

  Language:Jupyter Notebook1

• Tarun2199/Animal-Incursion-Detection-System

  An intrusion detection system (IDS) is a device or software application that monitors a network or systems for malicious activity or policy violations. Agile detection methods for the purpose of real time object detection. Faster R-CNN and SSD-MobileNet are used to train the model.

  Language:Python44

• Swastik-25/Imbalanced-Data-with-SMOTE-Techniques

  This repository contains implementation of some techniques like SMOTE, ADASYN, SMOTE + Tomek Links, SMOTE + ENN to overcome class imbalance in a binary classification problem.

  Language:Jupyter Notebook3822

• ccastore/SMOTE-ENN_out

  Oversamplng method modification SMOTE-ENN

  Language:Python51

• NOVA-IMS-Innovation-and-Analytics-Lab/geometric-smote

  Implementation of the Geometric SMOTE over-sampling algorithm.

  Language:Python3116

• carvalhoamc/DTO-SMOTE

  DTOSMOTE Experiments

  Language:Python43

• majobasgall/smote-bd

  SMOTE-BD: A distributed Synthetic Minority Oversampling Technique (SMOTE) for Big Data.

  Language:Scala91

• tgsmith61591/smrt

  Handle class imbalance intelligently by using variational auto-encoders to generate synthetic observations of your minority class.

  Language:Python12427

• analyticalmindsltd/smote_variants

  A collection of 85 minority oversampling techniques (SMOTE) for imbalanced learning with multi-class oversampling and model selection features

  Language:Jupyter Notebook615138

• wzy-enable/IDS-wzy

  IDS experiment

  Language:Python11

• rishabh-mondal/Evaluating-Shallow-and-Deep-Neural-Networks-for-Network-Intrusion-Detection-Systems-

  Intrusion detection system (IDS) has become an essential layer in all the latest ICT system due to an urge towards cyber safety in the day-to-day world. Reasons including uncertainty in finding the types of attacks and increased the complexity of advanced cyber attacks, IDS calls for the need of integration of Deep Neural Networks (DNNs). In this paper, DNNs have been utilized to predict the attacks on Network Intrusion Detection System (N-IDS). A DNN with 0.1 rate of learning is applied and is run for 1000 number of epochs and KDDCup-’99’ dataset has been used for training and benchmarking the network. For comparison purposes, the training is done on the same dataset with several other classical machine learning algorithms and DNN of layers ranging from 1 to 5. The results were compared and concluded that a DNN of 3 layers has superior performance over all the other classical machine learning algorithms.

  Language:Python61

• sgamage2/dl_ids_survey

  Deep learning models for network intrusion detection

  Language:Python3117

• FrazHackz/Network-Intrusion-Detection-System-Deep-Learning

  Neural Network based Intrusion Detection System (NIDS) on Intrusion Detection Evaluation Dataset (CICIDS2017)

  Language:Jupyter Notebook111

• UditVarshneyUV/Instrusion-Detection-System

  An Intrusion Detection System Project based on Machine Learning Techniques using Recurrent Neural Network.

  Language:Jupyter Notebook4

• EmrahTfn/Anomaly-Based_Intrusion_Detection_Case_Study

  Code repository for the article "Anomaly-Based Intrusion Detection in an Institutional Network Using Machine Learning: A Case Study on Probing Attacks"

  Language:Python1