Dataset to Train Intrusion Detection Systems based on Machine Learning Models for Electrical Substations
Authors/Creators
Description
DATASET
This dataset is part of the research work titled "A dataset to train intrusion detection systems based on machine learning models for electrical substations". The dataset has been meticulously curated to support the development and evaluation of machine learning models tailored for detecting cyber intrusions in the context of electrical substations. It is intended to facilitate research and advancements in cybersecurity for critical infrastructure, specifically focusing on real-world scenarios within electrical substation environments. We encourage its use for experimentation and benchmarking in related areas of study.
The code name of the dataset is SANDI-2024 (Substation Anomaly Network Data for Intrusion detection 2024)
The following sections list the content of the dataset generated.
Data
- raw
- iec6180
- attack-free-data
- capture61850-attackfree.pcap (from real substation)
- capture61850-attackfree_PTP.pcap
- capture61850-attackfree_normalfault.pcap
- attack-data
- capture61850-floodattack_withfault.pcap
- capture61850-floodattack_withoutfault.pcap
- capture61850-fuzzyattack_withfault.pcap
- capture61850-fuzzyattack_withoutfault.pcap
- capture61850-replay.pcap
- capture61850-ptpattack.pcap
- attack-free-data
- iec104
- attack-free-data
- capture104-attackfree.pcap (from real substation)
- attack-data
- capture104-dosattack.pcap
- capture104-floodattack.pcap
- capture104-fuzzyattack.pcap
- capture104-iec104starvationattack.pcap
- capture104-mitmattack.pcap
- capture104-ntpddosattack.pcap
- capture104-portscanattack.pcap
- attack-free-data
- iec6180
- processed
- iec6180
- attack-free-data
- capture61850-attackfree.csv
- capture61850-attackfree_PTP.csv
- capture61850-attackfree_normalfault.csv
- attack-data
- capture61850-floodattack_withfault.csv
- capture61850-floodattack_withoutfault.csv
- capture61850-fuzzyattack_withfault.csv
- capture61850-fuzzyattack_withoutfault.csv
- capture61850-replay.csv
- capture61850-ptpattack.csv
- headers_iec61850[all].txt
- attack-free-data
- iec104
- attack-free-data
- capture104-attackfree.csv
- attack-data
- capture104-dosattack.csv
- capture104-floodattack.csv
- capture104-fuzzyattack.csv
- capture104-iec104starvationattack.csv
- capture104-mitmattack.csv
- capture104-ntpddosattack.csv
- capture104-portscanattack.csv
- headers_iec104[all].txt
- attack-free-data
- iec6180
Description
- file type: it may be captured61850 or captured104 depending on whether it contains network captures of the protocol IEC61850 or IEC104.
- attack: attack free (attackfree) or attack name is added to the file name.
- function: optionally, if there are some details about functionality captured (normalfault) or specific protocol capture (PTP).
- file extension: the type can be PCAP (network capture) or CSV (flow file).
Results
- results
- test1-iec104
- model-test1-iec104.pkl
- test1-iec104.log
- test1-iec61850
- model-test1-iec61850.pkl
- test1-iec61850.log
- test2-iec61850
- model-test2-iec61850.pkl
- test2-iec61850.log
- test1-iec104
Description
The outcomes of different test executions are available as follows:
- test1-iec104: IEC 104 protocol for all attacks and attack free scenario
- test1-iec61850: IEC 61850 protocol for fuzzy attack with fault injection and attack free scenario
- test2-iec61850: IEC 61850 protocol for fuzzy attack normal operation and attack free scenario
Each test consists of the model results in Python pickle format (with a .pkl extension) and a detailed description of the execution conditions in an output log file (with a .log extension).
Source Code
Tools to process network captures from IEC61850 and IEC104 can be found at github repository.
Files
README.md
Files
(1.2 GB)
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Additional details
Additional titles
- Subtitle
- SANDI-2024 (Substation Anomaly Network Data for Intrusion detection 2024)
Funding
- European Commission
- eFORT - Establishment of a FramewORk for Transforming current EPES into a more resilient, reliable and secure system all over its value chain 101075665
- Ministerio de Ciencia, Innovación y Universidades
- MIMFA TED2021-131115A-I00
- European Commission
- Proyecto Estratégico CIBERSEGURIDAD EINA UNIZAR (funded by Spanish National Cybersecurity Institute)
- Gobierno de Aragón
- Programa de Proyectos Estratégicos de Grupos de Investigación T21-23R
- Dutch Research Council
- RAPID CS.007
Software
- Repository URL
- https://github.com/esguti/cybersecurity-datasets
- Programming language
- Shell , Python
- Development Status
- Active