Enhanced Intrusion Detection for ICS Using MS1DCNN and Transformer to Tackle Data Imbalance
Yuanlin Zhang, Lei Zhang, Xiaoyuan Zheng · 2024
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Description
Yuanlin Zhang, Lei Zhang, and Xiaoyuan Zheng build an intrusion detector for industrial control networks, in a paper from two thousand twenty-four. Attacks on programmable logic controllers can throw factories and utilities into chaos. Models that spot attacks find it hard, since attack traffic is rare next to normal traffic.
The team first put together a dataset with five attack types aimed at controllers. Oversampling methods, SMOTE and its borderline variant, fattened the minority classes to a fair size. Their detector pulls out features through two channels. A multi-scale one-dimensional convolutional network reads fine temporal patterns in the flow. A weight-dropped transformer catches the longer shape of the traffic. To join the two lifted detection when the data has a long-tail distribution.
Catalog record
| CREATOR | Yuanlin Zhang, Lei Zhang, Xiaoyuan Zheng |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 49 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |