| --- |
| license: mit |
| task_categories: |
| - tabular-classification |
| tags: |
| - cybersecurity |
| - malware-detection |
| - phishing-detection |
| - infrastructure-metadata |
| - domains |
| pretty_name: MIAF Domain Detection Infrastructure Datasets |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| # MIAF: Domain Detection Infrastructure Datasets |
|
|
| This dataset collection serves as the standardized evaluation benchmark for MIAF. It consists of nine classification datasets derived from four major public malicious-domain benchmarks. |
|
|
| ## Overview |
|
|
| We evaluate MIAF across nine classification datasets derived from four public malicious-domain benchmarks: |
| - **DomainRadar** (Hranicky et al., 2025) |
| - **ThreatFox** (Abuse.ch, 2025) |
| - **DeepURLBench** (Schvartzman et al., 2024) |
| - **MACFormer** (2025) |
|
|
| These datasets cover malware detection, phishing detection, and long-tailed malware-family attribution. The benchmarks span diverse characteristics in terms of scale, class balance, label granularity, and metadata availability, enabling an evaluation of the efficacy of infrastructure metadata under varied operating conditions. |
|
|
| ## Data Splits and Reorganization |
|
|
| To establish a consistent evaluation baseline, we have reorganized each benchmark into task-specific subsets and partitioned them into disjoint **training**, **development**, and **testing** sets using a **60/20/20** ratio. This stratification was applied to every individual class within the datasets to ensure a fair and consistent baseline across all evaluated methods. |
|
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| All datasets that lacked native infrastructure metadata (ThreatFox, DeepURLBench, and MACFormer) have been enriched using the uniform EDC pipeline. |
|
|
| ## Dataset Characteristics |
|
|
| | Dataset | Task | Samples | Classes | Mal. % (Train/Val/Test) | Metadata Source | |
| | :--- | :--- | :--- | :--- | :--- | :--- | |
| | **DomainRadar** | Malware (binary) | 341,935 | 2 (legit / malicious) | 19.1% | Native | |
| | | Phishing (binary) | 441,207 | 2 (legit / malicious) | 37.3% | Native | |
| | | Malware family (MC) | 311,906 | 61 (legit + 60 families) | 11.3% | Native | |
| | **ThreatFox** | Malware (binary) | 176,065 | 2 (legit / malicious) | 43.2% | EDC-enriched | |
| | | Malware family (MC) | 176,065 | 65 (legit + 64 families) | 43.2% | EDC-enriched | |
| | **DeepURLBench** | Malware (binary) | 375,917 | 2 (benign / mal) | 24.1% | EDC-enriched | |
| | | Phishing (binary) | 362,347 | 2 (benign / phishing) | 21.3% | EDC-enriched | |
| | **MACFormer** | Malware (binary) | 350,532 | 2 (legit / malicious) | 32.9% | EDC-enriched | |
| | | Phishing (binary) | 266,500 | 2 (legit / malicious) | 11.8% | EDC-enriched | |
|
|
| ## Structure |
|
|
| Inside each dataset folder, you will find: |
| - `train.csv`: Training split (60%) |
| - `dev.csv`: Development/Validation split (20%) |
| - `test.csv`: Testing split (20%) |
| - `*_ip.csv`: Corresponding infrastructure metadata (IP records) for each split. |
|
|
| ## Reproducibility |
|
|
| To facilitate reproducibility, we release this consolidated corpus of standardized metadata as a public resource. |
|
|
| **Link:** [https://huggingface.co/datasets/ahmedBargady/MIAF_DomainDetection_Infrastructure_Datasets](https://huggingface.co/datasets/ahmedBargady/MIAF_DomainDetection_Infrastructure_Datasets) |
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