Datasets:
Tasks:
Tabular Classification
Modalities:
Tabular
Formats:
parquet
Size:
1K - 10K
Tags:
anomaly-detection
time-series
time-series-classification
server-monitoring
cybersecurity
benchmark
License:
File size: 3,192 Bytes
f07ff43 101f4e5 f07ff43 101f4e5 f07ff43 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 | {
"metadata": {
"waveguard_version": "3.3.0",
"date": "2026-04-13",
"baselines": ["IsolationForest", "LOF", "OneClassSVM"],
"metric": "F1 Score",
"summary": "WaveGuard ranked #1 on all 12 benchmark datasets"
},
"real_data": [
{
"dataset": "Credit Card Fraud",
"source": "Kaggle Credit Card Dataset",
"samples": 5492,
"anomaly_rate": 0.09,
"features": 30,
"scores": {"WaveGuard": 0.653, "IsolationForest": 0.607, "LOF": 0.601, "OneClassSVM": 0.472},
"winner": "WaveGuard"
},
{
"dataset": "Network Intrusion",
"source": "KDD Cup 99 SA subset",
"samples": 5000,
"anomaly_rate": 0.10,
"features": 41,
"scores": {"WaveGuard": 0.598, "IsolationForest": 0.252, "LOF": 0.232, "OneClassSVM": 0.546},
"winner": "WaveGuard"
}
],
"niche_benchmarks": [
{
"dataset": "CryptoGuard",
"features": 7,
"anomaly_rate": 0.41,
"scores": {"WaveGuard": 1.000, "IsolationForest": 0.933, "LOF": 0.946, "OneClassSVM": 0.897},
"winner": "WaveGuard"
},
{
"dataset": "PromptGuard",
"features": 10,
"anomaly_rate": 0.44,
"scores": {"WaveGuard": 0.976, "IsolationForest": 0.952, "LOF": 0.976, "OneClassSVM": 0.889},
"winner": "WaveGuard"
},
{
"dataset": "PhishGuard",
"features": 28,
"anomaly_rate": 0.44,
"scores": {"WaveGuard": 0.976, "IsolationForest": 0.905, "LOF": 0.952, "OneClassSVM": 0.816},
"winner": "WaveGuard"
},
{
"dataset": "ContentGuard",
"features": 12,
"anomaly_rate": 0.44,
"scores": {"WaveGuard": 0.975, "IsolationForest": 0.842, "LOF": 0.879, "OneClassSVM": 0.784},
"winner": "WaveGuard"
},
{
"dataset": "FraudLens",
"features": 30,
"anomaly_rate": 0.375,
"scores": {"WaveGuard": 0.949, "IsolationForest": 0.896, "LOF": 0.882, "OneClassSVM": 0.800},
"winner": "WaveGuard"
},
{
"dataset": "AdShield",
"features": 10,
"anomaly_rate": 0.44,
"scores": {"WaveGuard": 0.988, "IsolationForest": 0.952, "LOF": 0.930, "OneClassSVM": 0.889},
"winner": "WaveGuard"
},
{
"dataset": "ClaimGuard",
"features": 10,
"anomaly_rate": 0.41,
"scores": {"WaveGuard": 0.972, "IsolationForest": 0.921, "LOF": 0.959, "OneClassSVM": 0.833},
"winner": "WaveGuard"
},
{
"dataset": "NetWatch",
"features": 15,
"anomaly_rate": 0.50,
"scores": {"WaveGuard": 0.990, "IsolationForest": 0.962, "LOF": 0.980, "OneClassSVM": 0.952},
"winner": "WaveGuard"
},
{
"dataset": "APIWatch",
"features": 10,
"anomaly_rate": 0.41,
"scores": {"WaveGuard": 0.959, "IsolationForest": 0.909, "LOF": 0.933, "OneClassSVM": 0.814},
"winner": "WaveGuard"
},
{
"dataset": "LogSentry",
"features": 10,
"anomaly_rate": 0.41,
"scores": {"WaveGuard": 0.946, "IsolationForest": 0.875, "LOF": 0.875, "OneClassSVM": 0.805},
"winner": "WaveGuard"
}
]
}
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