Code

• 基于机器学习的恶意流量检查平台，做成了平台

• NetworkTrafficAnalysis 网络流量分析代码

• 物联网-网络-入侵检测-和分类-使用-可解释-XAI-机器学习-算法
  IoT-Network-Intrusion-Detection-and-Classification-using-Explainable-XAI-Machine-Learning

  harshilpatel1799 • Updated Aug 15, 2023

• 物联网
  Iot-Cyber-Security-with-Machine-Learning-Research-Project

  harshilpatel1799 • Updated Aug 30, 2023

Paper

• A Deep Multi-Modal Cyber-Attack Detection in Industrial Control Systems
A Deep Multi-Modal Cyber-Attack Detection in Industrial Control Systems | Papers With Code

• 基于集成学习的加密恶意流量检测
基于集成学习的加密恶意流量检测 |施普林格链接 (springer.com)

• 一种基于半监督深度学习的网络恶意流量检测方法
一种基于半监督深度学习的网络恶意流量检测方法 |IEEE会议出版物 |IEEE Xplore

• 物联网网络中恶意流量检测的机器学习模型 物联网网络中恶意流量检测的机器学习模型 /IoT-23 数据集/ |施普林格链接 (springer.com)

• A Deep Hierarchical Network for Packet-Level Malicious Traffic Detection A Deep Hierarchical Network for Packet-Level Malicious Traffic Detection | IEEE Journals & Magazine | IEEE Xplore
  NetworkTrafficAnalysis

  bobolike123 • Updated Aug 1, 2023

• Machine Learning for Encrypted Malicious Traffic Detection: Approaches, Datasets and Comparative Study [2203.09332] Machine Learning for Encrypted Malicious Traffic Detection: Approaches, Datasets and Comparative Study (arxiv.org)

• An Input-Agnostic Hierarchical Deep Learning Framework for Traffic Fingerprinting

• CCS 2022 Exposing the Rat in the Tunnel: Using Traffic Analysis for Tor-based Malware Detection Exposing the Rat in the Tunnel | Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security
  tormalwarefp

  malfp • Updated Jul 17, 2023

• New Directions in Automated Traffic Analysis（自动化流量分析 CCS21） New Directions in Automated Traffic Analysis | Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security

• S&P 2022 2021 2020 没有相关论文

• NDSS 2023 BARS: Local Robustness Certification for Deep Learning based Traffic Analysis Systems
BARS: Local Robustness Certification for Deep Learning based Traffic Analysis Systems - NDSS Symposium (ndss-symposium.org)
BARS
KaiWangGitHub • Updated May 3, 2023

• NDSS 2021 FlowLens: Enabling Efficient Flow Classification for ML-based Network Security Applications FlowLens: Enabling Efficient Flow Classification for ML-based Network Security Applications - NDSS Symposium (ndss-symposium.org)
  FlowLens

  dmbb • Updated Jun 21, 2023

• NDSS 2020 Encrypted DNS –> Privacy? A Traffic Analysis Perspective Encrypted DNS -> Privacy? A Traffic Analysis Perspective - NDSS Symposium (ndss-symposium.org)

• NDSS 2020 Practical Traffic Analysis Attacks on Secure Messaging Applications Practical Traffic Analysis Attacks on Secure Messaging Applications - NDSS Symposium (ndss-symposium.org)

• USENIX 2022 Automated Detection of Automated Traffic
Automated Detection of Automated Traffic | USENIX

• Adaptive Clustering-based Malicious Traffic Classification at the Network Edge Infocom 2021 Adaptive Clustering-based Malicious Traffic Classification at the Network Edge | IEEE Conference Publication | IEEE Xplore
  ACID

  Mobile-Intelligence-Lab • Updated Aug 24, 2023

• Poisoning Attacks on Deep Learning based Wireless Traffic Prediction INFOCOM 2022 Poisoning Attacks on Deep Learning based Wireless Traffic Prediction | IEEE Conference Publication | IEEE Xplore

• TrojanFlow: A Neural Backdoor Attack to Deep Learning-based Network Traffic Classifiers INFOCOM 2022 TrojanFlow: A Neural Backdoor Attack to Deep Learning-based Network Traffic Classifiers | IEEE Conference Publication | IEEE Xplore
  🗒️
  TrojanFlow: A Neural Backdoor Attack to Deep Learning-based Network Traffic Classifiers
  TrojanNN

  PurduePAML • Updated Aug 20, 2023
  （其他论文关于神经后门的Code).

• SoK: Pragmatic Assessment of Machine Learning for Network Intrusion Detection（关于机器学习用于网络入侵检测的研究） [2305.00550] SoK: Pragmatic Assessment of Machine Learning for Network Intrusion Detection (arxiv.org)

• FlowTransformer: A Transformer Framework for Flow-based Network Intrusion Detection Systems [2304.14746] FlowTransformer: A Transformer Framework for Flow-based Network Intrusion Detection Systems (arxiv.org)

• NDSS 2018 Kitsune: An Ensemble of Autoencoders for Online Network Intrusion Detection 运用自编码无监督入侵检测识别 Kitsune: An Ensemble of Autoencoders for Online Network Intrusion Detection. (readpaper.com) Code ymirsky/Kitsune-py: A network intrusion detection system based on incremental statistics (AfterImage) and an ensemble of autoencoders (KitNET) (github.com)

• NDSS 2018 Trojaning Attack on Neural Networks (purdue.edu)
  TrojanNN

  PurduePAML • Updated Aug 20, 2023
  INFOCOM 2022后门攻击的原始代码

• CVPR 2023 神经网络后门 CVPR 2023 Open Access Repository (thecvf.com)
  ARCHITECTURAL-BACKDOORS-IN-NEURAL-NETWORKS

  QuangNguyen2609 • Updated Aug 24, 2023

• Federated-Learning-Based-Intrusion-Detection-System

  iZRJ • Updated Aug 2, 2023
  基于联邦学习的入侵检测系统，用的最基本的FedAvg，可以作为code基础

• Generalizing intrusion detection for heterogeneous networks: A stacked-unsupervised federated learning approach | Papers With Code 异构网络的泛化入侵检测：一种堆叠无监督的联邦学习方法，考虑到了FL中的异构问题

• ConFlow

  AshinWang • Updated Jun 13, 2023
  对比网络流改善网络入侵检测中的类不平衡学习 可能会用在FL中，因为类不平衡，FL中常见

流量分析工具

• zeek The Zeek Network Security Monitor

• Ettercap Ettercap Home Page (ettercap-project.org)

• Wireshark

数据集

• IDS 2018 用于入侵检测系统的数据集，用于研究和评估网络安全领域的算法和模型。该数据集收集了大规模的网络通信数据，包含了来自真实网络环境中的正常流量和各种类型的网络攻击流量。 https://www.unb.ca/cic/datasets/ids-2018.html

数据预处理

• RawNetworkDataPreProcessing

  alothman • Updated Feb 2, 2023
  Raw Network Traffic Data Preprocessing and Preparation for Automatic Analysis | IEEE Conference Publication | IEEE Xplore

• pcap_preprocessor

  gghg1989 • Updated Feb 16, 2022

• irini90/pcap_preprocessing: Scripts to extract packet features from pcap files and generate arffs for AI purposes (github.com)

• CapCSV-meter

  maliksh7 • Updated Aug 30, 2022

• PcapPreprocessor

  kevingbrady • Updated Feb 21, 2022

神经后门

• stux-DNN

  bryankim96 • Updated Apr 7, 2023

• robbycostales/live-trojans: Code for "Live Trojan Attacks on Deep Neural Networks" paper (github.com)

• 通过GAN

暑假论文

• Poisoning Attacks and Data Sanitization Mitigations for Machine Learning Models in Network Intrusion Detection Systems（已读完，无代码）

• VulnerGAN: a backdoor attack through vulnerability amplification against machine learning-based network intrusion detection systems
  VulnerGAN-py

  liuguangrui-hit • Updated Jul 25, 2023

• Adversarial Network Traffic: Towards Evaluating the Robustness of Deep Learning-Based Network Traffic Classification
  AdversarialNetworkTraffic

  amsadeghzadeh • Updated Aug 13, 2023