A Practical, Lightweight Deep Learning Solution for DDoS Attack Detection

这是一个基于Python的网络入侵检测与防御系统，提供实时流量分析、攻击检测、自动防御和可视化监控功能。

Adaptive Federated Learning Approach to DDoS attack detection

大模型基础: 一文了解大模型基础知识

本项目旨在分享大模型相关技术原理以及实战经验（大模型工程化、大模型应用落地）

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

Network Intrusion Detection based on various machine learning and deep learning algorithms using UNSW-NB15 Dataset

A novel Intrusion Detection and Prevention System (IDPS) using Deep Reinforcement Learning (DRL) for IoT networks. This project detects and classifies cyber threats using a machine learning pipelin…

Adversarial Attacks and Defenses in Deep Reinforcement Learning: A Comprehensive Evaluation in a Highway Environment

Automated Heterogeneous IoT Attack Detection through Deep Reinforcement Learning: A Dynamic Machine Learning Approach

SquirRL: Automating Attack Discovery on Blockchain Incentive Mechanisms with Deep Reinforcement Learning

Code for the master project: use DRL for intrusion detection

Code for the NeurIPS 2023 Paper: Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms

Corresponding code to the paper "Enhancing the Transferability of Adversarial Attacks via Multi-Feature Attention"

[ICDM 2020] Meta-AAD: Active Anomaly Detection with Deep Reinforcement Learning

Anomaly based Instrusion Detection System using RNN-LSTMs. Datasets include NSL-KDD and UNSW-NB15.

Development of Botnet Detection Module for Traffic-Based IoT Devices Using Deep Learning

MACTA: A Multi-agent Reinforcement Learning Approach for Cache Timing Attacks and Detection

Repository for "RRIoT: Recurrent Reinforcement Learning for Cyber Threat Detection on IoT Devices"

Using RL for anomaly detection in NSL-KDD

This repo is an extension to the novel approach for detection and mitigation of insider attacks using reinforcement learning using deep reinforcement learning. In this repository we have included d…

Code for intrusion detection system (IDS) development using CNN models and transfer learning

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

This project uses Deep Q-Networks (DQN), a reinforcement learning technique, to detect phishing URLs. It extracts features from URL structures and trains a DQN agent to classify URLs as legitimate …

Massively Parallel Deep Reinforcement Learning. 🔥

Deep Reinforcement Learning for Keras.

A fork of OpenAI Baselines, implementations of reinforcement learning algorithms