Research on controller area network Intrusion Detection Systems

Overview

Group members information

Member 1: Lixue Liang

Member 2: Yuet Lee Chan

Member 3: Xinruo Zhang

Member 4: Yifei Han

User Manual

Generate Attack Packets

  1. To generate Dos attack packets, run ‘python3.8 Dos_SameIDSameFrameLength(Dos).py’.
  2. To generate Fuzzy attack packets, run ‘python3.8 Format_RandomLog_Generator(Fuzzy).py’.
  3. To generate Spoofing attack packets, run ‘python3.8 spoofing.py’

Generate Normal CAN Bus traffic on a virtual interface

  1. Open a terminal, run ‘python3.8 setup.py’ to set up the SocketCAN interface and ready for sending CAN Bus traffic. Modify the filenames inside the file before use. If there is ‘0x’ before the ID in a normal traffic CSV file, run ‘python3.8 preprocess_traffic.py’ before setting up the normal traffic.

Generate Attack CAN Bus traffic on a selected virtual interface

  1. To generate the attack traffic, open a new terminal(s), run ‘python3.8 attack.py’, and follow the instructions.

Capture traffic by Wireshark and Format the exported CSV file

  1. After running setup.py, before starting any traffic, open a terminal, run ‘sudo wireshark’ to capture packets. The Wireshark must run as administrator, otherwise, the virtual interface won’t show.
  2. Export collected traffic to a CSV file from Wireshark.
  3. Run ‘python3.8 format_wireshark.py’ to format the exported CSV file. Modify the filenames inside the file before use.
  4. Run ‘python3.8 MarkType.py’ to mark the normal traffic and attack traffic.

Traffic Visualization

  1. Run ‘python3.8 MatPlot.py’ to view the plot diagram and bar diagram of the selected CAN ID.

Data Processing and ID3 Model Training & Testing

  1. Run ‘python3.8 ids_data_processing.py’ to convert ID and data fields from hexadecimal to decimal, and combine data fields into one column.
  2. Run ‘ID3_model.ipynb’ to train and test the accuracy of the model.

Check outliers

  1. Import the attack csv file into folder
  2. Run 'outliers.R' to mark the 1 and 0 in a new colunm and generate a new csv file.
Owner
Roche
Roche
Unofficial implementation of Google "CutPaste: Self-Supervised Learning for Anomaly Detection and Localization" in PyTorch

CutPaste CutPaste: image from paper Unofficial implementation of Google's "CutPaste: Self-Supervised Learning for Anomaly Detection and Localization"

Lilit Yolyan 59 Nov 27, 2022
Practical tutorials and labs for TensorFlow used by Nvidia, FFN, CNN, RNN, Kaggle, AE

TensorFlow Tutorial - used by Nvidia Learn TensorFlow from scratch by examples and visualizations with interactive jupyter notebooks. Learn to compete

Alexander R Johansen 1.9k Dec 19, 2022
Zero-Shot Text-to-Image Generation VQGAN+CLIP Dockerized

VQGAN-CLIP-Docker About Zero-Shot Text-to-Image Generation VQGAN+CLIP Dockerized This is a stripped and minimal dependency repository for running loca

Kevin Costa 73 Sep 11, 2022
Image process framework based on plugin like imagej, it is esay to glue with scipy.ndimage, scikit-image, opencv, simpleitk, mayavi...and any libraries based on numpy

Introduction ImagePy is an open source image processing framework written in Python. Its UI interface, image data structure and table data structure a

ImagePy 1.2k Dec 29, 2022
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥

face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa

Zhao Jian 3.1k Jan 04, 2023
EFENet: Reference-based Video Super-Resolution with Enhanced Flow Estimation

EFENet EFENet: Reference-based Video Super-Resolution with Enhanced Flow Estimation Code is a bit messy now. I woud clean up soon. For training the EF

Yaping Zhao 19 Nov 05, 2022
Source for the paper "Universal Activation Function for machine learning"

Universal Activation Function Tensorflow and Pytorch source code for the paper Yuen, Brosnan, Minh Tu Hoang, Xiaodai Dong, and Tao Lu. "Universal acti

4 Dec 03, 2022
PyTorch implementation of 1712.06087 "Zero-Shot" Super-Resolution using Deep Internal Learning

Unofficial PyTorch implementation of "Zero-Shot" Super-Resolution using Deep Internal Learning Unofficial Implementation of 1712.06087 "Zero-Shot" Sup

Jacob Gildenblat 196 Nov 27, 2022
A set of simple scripts to process the Imagenet-1K dataset as TFRecords and make index files for NVIDIA DALI.

Overview This is a set of simple scripts to process the Imagenet-1K dataset as TFRecords and make index files for NVIDIA DALI. Make TFRecords To run t

8 Nov 01, 2022
A custom DeepStack model that has been trained detecting ONLY the USPS logo

This repository provides a custom DeepStack model that has been trained detecting ONLY the USPS logo. This was created after I discovered that the Deepstack OpenLogo custom model I was using did not

Stephen Stratoti 9 Dec 27, 2022
Code for our paper "Graph Pre-training for AMR Parsing and Generation" in ACL2022

AMRBART An implementation for ACL2022 paper "Graph Pre-training for AMR Parsing and Generation". You may find our paper here (Arxiv). Requirements pyt

xfbai 60 Jan 03, 2023
A Python package for faster, safer, and simpler ML processes

Bender 🤖 A Python package for faster, safer, and simpler ML processes. Why use bender? Bender will make your machine learning processes, faster, safe

Otovo 6 Dec 13, 2022
A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch

Introduction This is a Python package available on PyPI for NVIDIA-maintained utilities to streamline mixed precision and distributed training in Pyto

Artit 'Art' Wangperawong 5 Sep 29, 2021
PED: DETR for Crowd Pedestrian Detection

PED: DETR for Crowd Pedestrian Detection Code for PED: DETR For (Crowd) Pedestrian Detection Paper PED: DETR for Crowd Pedestrian Detection Installati

36 Sep 13, 2022
This repository contains python code necessary to replicated the experiments performed in our paper "Invariant Ancestry Search"

InvariantAncestrySearch This repository contains python code necessary to replicated the experiments performed in our paper "Invariant Ancestry Search

Phillip Bredahl Mogensen 0 Feb 02, 2022
Sequence modeling benchmarks and temporal convolutional networks

Sequence Modeling Benchmarks and Temporal Convolutional Networks (TCN) This repository contains the experiments done in the work An Empirical Evaluati

CMU Locus Lab 3.5k Jan 01, 2023
Benchmark tools for Compressive LiDAR-to-map registration

Benchmark tools for Compressive LiDAR-to-map registration This repo contains the released version of code and datasets used for our IROS 2021 paper: "

Allie 9 Nov 24, 2022
KE-Dialogue: Injecting knowledge graph into a fully end-to-end dialogue system.

Learning Knowledge Bases with Parameters for Task-Oriented Dialogue Systems This is the implementation of the paper: Learning Knowledge Bases with Par

CAiRE 42 Nov 10, 2022
Tensorflow implementation of "Learning Deep Features for Discriminative Localization"

Weakly_detector Tensorflow implementation of "Learning Deep Features for Discriminative Localization" B. Zhou, A. Khosla, A. Lapedriza, A. Oliva, and

Taeksoo Kim 363 Jun 29, 2022
PyTorch implementations of the paper: "DR.VIC: Decomposition and Reasoning for Video Individual Counting, CVPR, 2022"

DRNet for Video Indvidual Counting (CVPR 2022) Introduction This is the official PyTorch implementation of paper: DR.VIC: Decomposition and Reasoning

tao han 35 Nov 22, 2022