Project publication · Frontiers in Computer Science
Summary
The article presents TRUST Lab, a CICFlowMeter dataset for evaluating intrusion detection systems in IoT and edge scenarios with unambiguous labels.
Bibliometric indicators
JCR quartileQ3
Impact factor2.7
Google Scholar citations0
- JCR area
- Computer Science, Interdisciplinary Applications
- JCR year
- 2024
- Scholar query
- 21 May 2026
Main contribution
The main contribution is a capture methodology based on single-class sessions, with benign traffic or one isolated attack family in each window. The result includes 4.6 million bi-flows and 15 attack families, avoiding temporal contamination between classes.
Link with BoND1
For BoND1, the work strengthens the security and trust dimension in advanced IoT infrastructures. The dataset makes it easier to compare lightweight IDS models deployable at the edge, a useful element for non-cellular and B6G networks with autonomous-operation requirements.