JackKu0

JackKu0's Stars

• mlabonne/llm-course

  Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

  Language:Jupyter Notebook39.7k413684.2k

• RUCAIBox/LLMSurvey

  The official GitHub page for the survey paper "A Survey of Large Language Models".

  Language:Python10.6k15864824

• yangjianxin1/Firefly

  Firefly: 大模型训练工具，支持训练Qwen2.5、Qwen2、Yi1.5、Phi-3、Llama3、Gemma、MiniCPM、Yi、Deepseek、Orion、Xverse、Mixtral-8x7B、Zephyr、Mistral、Baichuan2、Llma2、Llama、Qwen、Baichuan、ChatGLM2、InternLM、Ziya2、Vicuna、Bloom等大模型

  Language:Python5.9k56280530

• NTMC-Community/MatchZoo

  Facilitating the design, comparison and sharing of deep text matching models.

  Language:Python3.8k176463900

• teler-sh/teler

  Real-time HTTP Intrusion Detection

  Language:Go3k5169252

• Western-OC2-Lab/Intrusion-Detection-System-Using-Machine-Learning

  Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)

  Language:Jupyter Notebook425116113

• Albertsr/Anomaly-Detection

  UnSupervised and Semi-Supervise Anomaly Detection / IsolationForest / KernelPCA Detection / ADOA / etc.

  Language:Python2919689

• OWASP/SecureTea-Project

  The OWASP SecureTea Project provides a one-stop security solution for various devices (personal computers / servers / IoT devices)

  Language:JavaScript2912765141

• eastmountyxz/AI-Security-Paper

  This resource mainly counts papers related to APT attacks, including APT traceability, APT knowledge graph construction, APT malicious sample detection, and APT overview. Hope these summarized papers are helpful to you~

  2015026

• AFAgarap/gru-svm

  [ICMLC 2018] A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection

  Language:Python16011639

• integeruser/CASIA-HWDB1.1-cnn

  Convolutional neural networks with Python 3 and Keras

  Language:Python1006530

• Rocionightwater/ML-NIDS-for-SCADA

  In this work, we aim at developing a NIDS (Network Intrusion Detection System) that detects attacks targeting SCADA systems, in a concrete industrial used case scenario.

  Language:Python666437

• munhouiani/LuNet

  Pytorch implementation of LuNet: A Deep Neural Network for Network Intrusion Detection

  Language:Python53216

• dendyikbc/kdd99-cnn-1

  Intrusion Detection Based on Convolutional Neural Network with kdd99 data set

  Language:Python522613

• TGyAlDeen/IDS-UNSW-NB15

  IoT intrusion Detection Model based on neural network and random forests

  Language:Jupyter Notebook433219

• racsa-lab/Edge-Detect

  Repository for IEEE CCNC'21 paper titled "Edge-Detect: Edge-centric Network Intrusion Detection using Deep Neural Network".

  Language:Python424210

• Jumabek/net_intrusion_detection

  Network intrusion detection with Machine Learning (Deep Learning) experiment : 1d-cnn, softmax, neural networks, convolution

  Language:Jupyter Notebook414014

• Shaik-Sohail-72/Network-Intrusion-Detection-Using-Deep-Learning

  Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning (RNN) models, MERN web I/O System.

  Language:EJS392114

• TheAxeC/machine-learning-techniques-for-flow-based-network-intrusion-detection-systems

  My Bachelor thesis for the Bachelor Computer Science (2015-2016) at UHasselt: An Intrusion detection system using machine learning approaches [Finished]

  Language:TeX393110

• pthevenet/Simple-NIDS

  Simple Network Intrusion Detection System. In python with Scapy.

  Language:Python356113

• 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

  Language:Jupyter Notebook325214

• Chandrahas-Soman/Simple_IDS_using_RYU_SDN_controller_and_Machine_Learning

  Implemented a network intrusion detection system for a software defined network using Random Forest method for classification of port and flow statistics.

  Language:Python232210

• sayanbanerjee992/Network-based-Intrusion-Detection-System

  The case study on a Network-based Intrusion Detection System is a Machine Learning-based Web application based on https://arxiv.org/pdf/1903.02460.pdf research paper. I have performed both binary and multi-class classification to predict the presence of any intrusion-based signal. If present, then which type of signal is present in the network. I have used various techniques like under sampling and over sampling because of the imbalances in the dataset, then train the model using Machine Learning techniques like Logistic Regression, Random Forest, XGBoost. Lastly built a web application and deploy it to AWS using AWS EC2 instance

  Language:Jupyter Notebook21104

• Tanmengxuan/ANID

  Attention Model for Network Intrusion Detection

  Language:Jupyter Notebook17404

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

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

  Language:Jupyter Notebook12101

• Battlingboy/AE-IDS

  Network Intrusion Detection System(Abnormal Detection)

  Language:Python11136

• mansipatel2508/Network-Intrusion-Detection-with-Feature-Extraction-ML

  The given information of network connection, model predicts if connection has some intrusion or not. Binary classification for good and bad type of the connection further converting to multi-class classification and most prominent is feature importance analysis.

  Language:Jupyter Notebook11210

• sampathv95/Network-Intrusion-Detection

  Autoencoder approach to detect attacks/intrusions in a network

  Language:Jupyter Notebook8114

• voyagerhui/WriterIdentification

  Writer identification based on CASIA-HWDB1.1

  Language:Python6010

• girgismicheal/Network-Intrusion-Detection-using-DeepLearning

  Language:Jupyter Notebook5101