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Fig 1.

Training Process Flowchart for AnomLocal.

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Table 1.

Important Features of the UNSW-NB15 Dataset.

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Fig 2.

Architectural diagram of Proposed Model.

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Table 2.

Detailed Neural Network Architecture of AnomLocal.

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Fig 3.

System Model Diagram of Proposed Model.

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Table 3.

Evaluation Metrics and Formulas.

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Table 4.

Accuracy Results for AnomLocal.

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Fig 4.

Accuracy Comparison across Different Models.

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Table 5.

Precision Results for AnomLocal.

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Fig 5.

Precision Metrics for Proposed Models.

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Table 6.

Recall Results for AnomLocal.

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Fig 6.

Recall Performance Evaluation across Detection Models.

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Table 7.

F1-Score Results for AnomLocal.

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Fig 7.

F1-Score Distribution among Different Anomaly Detection Models.

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Table 8.

False Positive Rate (FPR) for AnomLocal.

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Fig 8.

False Positive Rate (FPR) Analysis for Comparative Models.

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Table 9.

Detection Latency for AnomLocal.

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Fig 9.

Latency Reduction across Anomaly Detection Models.

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Table 10.

AUC-ROC for AnomLocal.

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Fig 10.

Comparative AUC-ROC Analysis AnomLocal.

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Fig 11.

Confusion Matrix for AnomLocal.

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Fig 12.

Overall Performance of AnomLocal Model.

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Table 11.

Comparison of AnomLocal with Recent Federated and Hybrid Anomaly Detection Models.

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Fig 13.

Performance Comparison of AnomLocal and Other Models.

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Table 12.

Cross-Validation Results for AnomLocal and Baseline Models.

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Table 13.

Performance across Different Data Splits.

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