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README.md

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+---
+pretty_name: Web Traffic Normal vs Anomalous
+language:
+- en
+license: mit
+task_categories:
+- text-classification
+tags:
+- cybersecurity
+- intrusion-detection
+- web-security
+- http
+- anomaly-detection
+size_categories:
+- 10K<n<100K
+---
+
+# Web Traffic Normal vs Anomalous
+
+A labeled HTTP request dataset for web traffic classification.
+
+This dataset contains raw HTTP requests collected into two classes:
+
+- `anomalous`: malicious or attack-like traffic
+- `normal`: benign traffic
+
+## Important note about data integrity
+
+The request payloads are kept as raw text. No normalization, decoding, truncation, lowercasing, header removal, or field cleaning was applied when creating the labeled files. The only added field is `label`.
+
+## Files
+
+Recommended files for Hugging Face Datasets:
+
+- `web_traffic_labeled_combined.jsonl`
+- `filtered_anomalous_traffic_labeled.jsonl`
+- `normalTrafficTest_clean_labeled.jsonl`
+
+Also included:
+
+- `web_traffic_labeled_combined.csv`
+- `filtered_anomalous_traffic_labeled.csv`
+- `normalTrafficTest_clean_labeled.csv`
+
+## Dataset schema
+
+Each example has the following fields:
+
+- `text` (`string`): full raw HTTP request, including line breaks
+- `label` (`string`): one of `anomalous` or `normal`
+
+### Example
+
+```json
+{
+  "text": "GET http://localhost:8080/tienda1/index.jsp HTTP/1.1\nUser-Agent: Mozilla/5.0 ...",
+  "label": "normal"
+}
+```
+
+## Class distribution
+
+- `anomalous`: 2,014
+- `normal`: 36,000
+- total: 38,014
+
+## Recommended usage
+
+This dataset is suitable for:
+
+- web attack detection
+- anomaly detection
+- HTTP request classification
+- WAF / IDS experimentation
+- baseline text classification benchmarks for cybersecurity
+
+## Loading with `datasets`
+
+### Load the combined JSONL file
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("json", data_files="web_traffic_labeled_combined.jsonl")
+print(dataset["train"][0])
+```
+
+### Load train/test splits from local files
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset(
+    "json",
+    data_files={
+        "train": "web_traffic_labeled_combined.jsonl",
+    },
+)
+```
+
+## Repository layout suggestion
+
+```text
+.
+├── README.md
+├── web_traffic_labeled_combined.jsonl
+├── filtered_anomalous_traffic_labeled.jsonl
+├── normalTrafficTest_clean_labeled.jsonl
+├── web_traffic_labeled_combined.csv
+├── filtered_anomalous_traffic_labeled.csv
+└── normalTrafficTest_clean_labeled.csv
+```
+
+## Limitations
+
+- The labels are binary only: `normal` and `anomalous`
+- The dataset may contain duplicated request patterns
+- The traffic appears to come from a web application testing context and may not cover all modern attack families
+- Credentials, hostnames, and request contents should be reviewed before production use
+
+## Citation
+
+If you publish work based on this dataset, please cite the dataset repository URL.