jogecodes/transformerAD
Code for the paper "Anomaly-Based Intrusion Detection in IIoT Networks Using Transformer Models"
This project helps industrial control system operators and security analysts detect unusual and potentially malicious activity in Industrial Internet of Things (IIoT) networks. It takes network traffic data from IIoT devices as input and outputs identified anomalies, helping to flag potential cyber intrusions. This is for professionals responsible for the security and operational integrity of critical industrial infrastructure.
No commits in the last 6 months.
Use this if you need to identify cyber-physical attacks or unusual behavior in your IIoT network traffic using advanced machine learning.
Not ideal if you are looking for a plug-and-play security product, as this requires technical expertise to set up and run.
Stars
36
Forks
5
Language
Jupyter Notebook
License
GPL-3.0
Category
Last pushed
Mar 03, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/jogecodes/transformerAD"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
GACWR/OpenUBA
A robust, and flexible open source User & Entity Behavior Analytics (UEBA) framework used for...
nfstream/nfstream
NFStream: a Flexible Network Data Analysis Framework.
echowei/DeepTraffic
Deep Learning models for network traffic classification
faucetsdn/poseidon
Poseidon is a python-based application that leverages software defined networks (SDN) to acquire...
CESNET/cesnet-datazoo
CESNET DataZoo: A toolset for large network traffic datasets