# Network Traffic Analysis on CICIoT2023 Proportion-shift Source: [Network Traffic Analysis on CICIoT2023 Proportion-shift]() Collection index: [llms.txt]() Data updated: 2026-02-26T05:31:18.594Z Evaluation of model performance for Network Traffic Analysis using the CICIoT2023 dataset under a proportion-shift setting, assessed using Accuracy (ACC), Macro Precision (M-PR), Macro Recall (M-RC), and Macro F1 Score (M-F1). A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. | Scope | Recorded value | | --- | --- | | Task | Network Traffic Analysis | | Dataset (including any stated split) | CICIoT2023 Proportion-shift | | Metric | Accuracy | | Unit | PERCENT | | Direction | Higher is better | | Results loaded | 7 of 7 | | Coverage | All results currently returned for this benchmark | Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol. ## Metrics - [Accuracy](): Higher is better; unit: PERCENT. - [Macro Precision](): Higher is better; unit: PERCENT. - [Macro Recall](): Higher is better; unit: PERCENT. - [Macro F1 Score](): Higher is better; unit: PERCENT. ## Recorded results | Method | Accuracy | Result date | Report paper | | --- | --- | --- | --- | | Traffic-MoE | 80.52 | Not recorded | 695b455a53fdd5c361742e4b | | ET-BERT | 78.34 | Not recorded | 695b455a53fdd5c361742e4b | | TrafficFormer | 75.59 | Not recorded | 695b455a53fdd5c361742e4b | | NetGPT | 75.35 | Not recorded | 695b455a53fdd5c361742e4b | | AppScanner | 72.32 | Not recorded | 695b455a53fdd5c361742e4b | | FS-Net | 69.37 | Not recorded | 695b455a53fdd5c361742e4b | | FlowPrint | 36.71 | Not recorded | 695b455a53fdd5c361742e4b | ### Traffic-MoE Accuracy: 80.52. Result ID: 6996f7bb5698665ec4447b23. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### ET-BERT Accuracy: 78.34. Result ID: 6996f7bb5698665ec4447b20. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### TrafficFormer Accuracy: 75.59. Result ID: 6996f7bb5698665ec4447b22. [Reporting paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### NetGPT Accuracy: 75.35. Result ID: 6996f7bb5698665ec4447b21. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### AppScanner Accuracy: 72.32. Result ID: 6996f7bb5698665ec4447b1d. [Reporting paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### FS-Net Accuracy: 69.37. Result ID: 6996f7bb5698665ec4447b1f. [Reporting paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### FlowPrint Accuracy: 36.71. Result ID: 6996f7bb5698665ec4447b1e. [Reporting paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. Page 1 of 1. This is an index page, not the full collection.