Generated: 2026-01-28 12:08:46
Total Test Runs: 6
Sources: Agent Evaluation: 6
| Metric | Value |
|---|---|
| Total Zero-Day Samples | 1217 |
| Zero-Day Attacks Detected | 1 |
| Zero-Day Attacks Missed | 1216 |
| Zero-Day False Alarms | 3 |
| Overall Detection Rate | 0.08% |
? Overall Performance: NEEDS IMPROVEMENT - Significant enhancement required
Total Detections: TP=3637, TN=0, FP=2363, FN=0
Test Sources: Agent Evaluation: 6
Zero-Day Detection Rate: 0.08%
| Source | Model | Date | Time | Filename | Total_Requests | Attack_Ratio | ZeroDay_Ratio | Accuracy | F1_Score | Precision | Recall | ZeroDay_Rate | ZeroDay_Precision | ZeroDay_False_Alarm_Rate | TP | FP | TN | FN | Total_Samples | ZeroDay_Detected | ZeroDay_Samples | ZeroDay_False_Alarms | ZeroDay_Missed | Avg_Response_Time | Test_Duration |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Agent Evaluation | Agent_Test | 2026-01-28 | 12:08:13 | metrics_20260128_120813.json | 1000 | 1.0 | 0.183 | 60.50% | 75.39% | 60.50% | 100.00% | 0.00% | 0.00% | 0.25% | 605 | 395 | 0 | 0 | 1000 | 0 | 183 | 1 | 183 | N/A | N/A |
| Agent Evaluation | Agent_Test | 2026-01-28 | 12:04:51 | metrics_20260128_120451.json | 1000 | 1.0 | 0.208 | 60.40% | 75.31% | 60.40% | 100.00% | 0.00% | 0.00% | 0.25% | 604 | 396 | 0 | 0 | 1000 | 0 | 208 | 1 | 208 | N/A | N/A |
| Agent Evaluation | Agent_Test | 2026-01-28 | 12:01:00 | metrics_20260128_120100.json | 1000 | 1.0 | 0.232 | 62.60% | 77.00% | 62.60% | 100.00% | 0.00% | 0.00% | 0.00% | 626 | 374 | 0 | 0 | 1000 | 0 | 232 | 0 | 232 | N/A | N/A |
| Agent Evaluation | Agent_Test | 2026-01-28 | 11:57:39 | metrics_20260128_115739.json | 1000 | 1.0 | 0.188 | 61.50% | 76.16% | 61.50% | 100.00% | 0.00% | 0.00% | 0.00% | 615 | 385 | 0 | 0 | 1000 | 0 | 188 | 0 | 188 | N/A | N/A |
| Agent Evaluation | Agent_Test | 2026-01-28 | 11:54:07 | metrics_20260128_115407.json | 1000 | 1.0 | 0.203 | 59.20% | 74.37% | 59.20% | 100.00% | 0.00% | 0.00% | 0.00% | 592 | 408 | 0 | 0 | 1000 | 0 | 203 | 0 | 203 | N/A | N/A |
| Agent Evaluation | Agent_Test | 2026-01-28 | 11:49:24 | metrics_20260128_114924.json | 1000 | 1.0 | 0.203 | 59.50% | 74.61% | 59.50% | 100.00% | 0.49% | 50.00% | 0.25% | 595 | 405 | 0 | 0 | 1000 | 1 | 203 | 1 | 202 | N/A | N/A |
================================================================================ C-NIDS DETECTOR - COMPREHENSIVE TEST REPORT ================================================================================ Report Generated: 2026-01-28 12:08:45 Total Test Runs: 6 Sources: 1 (Agent Evaluation) ================================================================================ OVERALL STATISTICS BY SOURCE: ---------------------------------------- Agent Evaluation: Total Runs: 6 Average Accuracy: 60.62% Average F1-Score: 75.47% Average Zero-Day Detection Rate: 0.08% Average Zero-Day Precision: 8.33% OVERALL STATISTICS: ---------------------------------------- Overall Average Accuracy: 60.62% Overall Average F1-Score: 75.47% Overall Zero-Day Detection Rate: 0.08% Overall Zero-Day Precision: 8.33% ZERO-DAY ATTACK ANALYSIS: ---------------------------------------- Total Zero-Day Samples: 1217 Zero-Day Attacks Detected: 1 Zero-Day Attacks Missed: 1216 Zero-Day False Alarms: 3 Overall Zero-Day Detection Rate: 0.08% Zero-Day False Alarm Rate: 0.13% TOTAL DETECTION COUNTS: ---------------------------------------- True Positives: 3637 True Negatives: 0 False Positives: 2363 False Negatives: 0 PER MODEL STATISTICS: ---------------------------------------- Agent_Test: Source: Agent Evaluation Latest Accuracy: 60.50% Latest F1-Score: 75.39% Zero-Day Rate: 0.08% Average Accuracy: 60.62% Average F1-Score: 75.47% Test Date: 2026-01-28 Latest Performance: FAIR RECOMMENDATIONS: ---------------------------------------- ?? Fair performance, room for improvement - Investigate high false positive/negative rates - Consider adding more training data - Review feature selection - Zero-day detection requires significant attention ? ZERO-DAY DETECTION CRITICAL ISSUES: - Implement additional anomaly detection techniques - Consider unsupervised learning approaches - Increase zero-day training scenarios - Review zero-day detection thresholds ================================================================================ END OF REPORT ================================================================================