Datasets:
Tasks:
Tabular Classification
Modalities:
Text
Languages:
English
Size:
1M - 10M
Tags:
cybersecurity
| dataset_info: | |
| features: | |
| - name: flow_id | |
| dtype: string | |
| - name: features | |
| struct: | |
| - name: src_port | |
| dtype: float32 | |
| - name: dst_port | |
| dtype: float32 | |
| - name: protocol | |
| dtype: float32 | |
| - name: flow_duration | |
| dtype: float32 | |
| - name: total_fwd_packet | |
| dtype: float32 | |
| - name: total_bwd_packets | |
| dtype: float32 | |
| - name: total_length_of_fwd_packet | |
| dtype: float32 | |
| - name: total_length_of_bwd_packet | |
| dtype: float32 | |
| - name: fwd_packet_length_max | |
| dtype: float32 | |
| - name: fwd_packet_length_min | |
| dtype: float32 | |
| - name: fwd_packet_length_mean | |
| dtype: float32 | |
| - name: fwd_packet_length_std | |
| dtype: float32 | |
| - name: bwd_packet_length_max | |
| dtype: float32 | |
| - name: bwd_packet_length_min | |
| dtype: float32 | |
| - name: bwd_packet_length_mean | |
| dtype: float32 | |
| - name: bwd_packet_length_std | |
| dtype: float32 | |
| - name: flow_bytes_per_s | |
| dtype: float32 | |
| - name: flow_packets_per_s | |
| dtype: float32 | |
| - name: flow_iat_mean | |
| dtype: float32 | |
| - name: flow_iat_std | |
| dtype: float32 | |
| - name: flow_iat_max | |
| dtype: float32 | |
| - name: flow_iat_min | |
| dtype: float32 | |
| - name: fwd_iat_total | |
| dtype: float32 | |
| - name: fwd_iat_mean | |
| dtype: float32 | |
| - name: fwd_iat_std | |
| dtype: float32 | |
| - name: fwd_iat_max | |
| dtype: float32 | |
| - name: fwd_iat_min | |
| dtype: float32 | |
| - name: bwd_iat_total | |
| dtype: float32 | |
| - name: bwd_iat_mean | |
| dtype: float32 | |
| - name: bwd_iat_std | |
| dtype: float32 | |
| - name: bwd_iat_max | |
| dtype: float32 | |
| - name: bwd_iat_min | |
| dtype: float32 | |
| - name: fwd_psh_flags | |
| dtype: float32 | |
| - name: bwd_psh_flags | |
| dtype: float32 | |
| - name: fwd_urg_flags | |
| dtype: float32 | |
| - name: bwd_urg_flags | |
| dtype: float32 | |
| - name: fwd_header_length | |
| dtype: float32 | |
| - name: bwd_header_length | |
| dtype: float32 | |
| - name: fwd_packets_per_s | |
| dtype: float32 | |
| - name: bwd_packets_per_s | |
| dtype: float32 | |
| - name: packet_length_min | |
| dtype: float32 | |
| - name: packet_length_max | |
| dtype: float32 | |
| - name: packet_length_mean | |
| dtype: float32 | |
| - name: packet_length_std | |
| dtype: float32 | |
| - name: packet_length_variance | |
| dtype: float32 | |
| - name: fin_flag_count | |
| dtype: float32 | |
| - name: syn_flag_count | |
| dtype: float32 | |
| - name: rst_flag_count | |
| dtype: float32 | |
| - name: psh_flag_count | |
| dtype: float32 | |
| - name: ack_flag_count | |
| dtype: float32 | |
| - name: urg_flag_count | |
| dtype: float32 | |
| - name: cwr_flag_count | |
| dtype: float32 | |
| - name: ece_flag_count | |
| dtype: float32 | |
| - name: down_per_up_ratio | |
| dtype: float32 | |
| - name: average_packet_size | |
| dtype: float32 | |
| - name: fwd_segment_size_avg | |
| dtype: float32 | |
| - name: bwd_segment_size_avg | |
| dtype: float32 | |
| - name: fwd_bytes_per_bulk_avg | |
| dtype: float32 | |
| - name: fwd_packet_per_bulk_avg | |
| dtype: float32 | |
| - name: fwd_bulk_rate_avg | |
| dtype: float32 | |
| - name: bwd_bytes_per_bulk_avg | |
| dtype: float32 | |
| - name: bwd_packet_per_bulk_avg | |
| dtype: float32 | |
| - name: bwd_bulk_rate_avg | |
| dtype: float32 | |
| - name: subflow_fwd_packets | |
| dtype: float32 | |
| - name: subflow_fwd_bytes | |
| dtype: float32 | |
| - name: subflow_bwd_packets | |
| dtype: float32 | |
| - name: subflow_bwd_bytes | |
| dtype: float32 | |
| - name: fwd_init_win_bytes | |
| dtype: float32 | |
| - name: bwd_init_win_bytes | |
| dtype: float32 | |
| - name: fwd_act_data_pkts | |
| dtype: float32 | |
| - name: fwd_seg_size_min | |
| dtype: float32 | |
| - name: active_mean | |
| dtype: float32 | |
| - name: active_std | |
| dtype: float32 | |
| - name: active_max | |
| dtype: float32 | |
| - name: active_min | |
| dtype: float32 | |
| - name: idle_mean | |
| dtype: float32 | |
| - name: idle_std | |
| dtype: float32 | |
| - name: idle_max | |
| dtype: float32 | |
| - name: idle_min | |
| dtype: float32 | |
| - name: semantic_flags | |
| struct: | |
| - name: high_packet_rate | |
| dtype: int8 | |
| - name: one_way_traffic | |
| dtype: int8 | |
| - name: syn_ack_imbalance | |
| dtype: int8 | |
| - name: uniform_packet_size | |
| dtype: int8 | |
| - name: long_idle_c2 | |
| dtype: int8 | |
| - name: label | |
| dtype: | |
| class_label: | |
| names: | |
| '0': benign | |
| '1': attack | |
| splits: | |
| - name: train | |
| num_bytes: 248127049 | |
| num_examples: 671088 | |
| - name: validation | |
| num_bytes: 62032886 | |
| num_examples: 167772 | |
| - name: test | |
| num_bytes: 77540185 | |
| num_examples: 209715 | |
| download_size: 119245598 | |
| dataset_size: 387700120 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| - split: validation | |
| path: data/validation-* | |
| - split: test | |
| path: data/test-* | |
| task_categories: | |
| - tabular-classification | |
| language: | |
| - en | |
| tags: | |
| - cybersecurity | |
| size_categories: | |
| - 1M<n<10M | |
| # CICFlow Binary Intrusion Detection Dataset | |
| ## Overview | |
| This dataset provides a **binary network intrusion detection (IDS) benchmark** derived from **CICFlowMeter flow-level features**. | |
| The task is to determine whether a given network flow is **benign** or **malicious**, making this dataset suitable for: | |
| * Practical IDS research | |
| * Rule-based and hybrid ML systems | |
| * High-imbalance classification experiments | |
| * Explainable security modeling | |
| --- | |
| ## Task | |
| **Binary classification** | |
| > *Given a network flow represented by CICFlowMeter features, predict whether it corresponds to an attack.* | |
| --- | |
| ## Labels | |
| | Label ID | Name | Description | | |
| | -------: | ------ | ----------------------------------------------- | | |
| | 0 | benign | Normal network traffic | | |
| | 1 | attack | Any malicious traffic (all attack types merged) | | |
| ### Label construction | |
| The binary label was derived by collapsing a multiclass IDS taxonomy: | |
| * `benign` → `0` | |
| * all attack categories → `1` | |
| No other transformations were applied to the labels. | |
| --- | |
| ## Dataset Structure | |
| ```text | |
| DatasetDict({ | |
| train, | |
| validation, | |
| test | |
| }) | |
| ``` | |
| Each split contains records with the following schema: | |
| ```text | |
| flow_id: string | |
| features: dict[str, float] | |
| semantic_flags: dict[str, int] | |
| label: ClassLabel (benign / attack) | |
| ``` | |
| --- | |
| ## Feature Description | |
| ### 1. Raw Numeric Features (`features`) | |
| The `features` field contains **flow-level statistics extracted by CICFlowMeter**. | |
| These include: | |
| #### Traffic volume & direction | |
| * `total_fwd_packets`, `total_bwd_packets` | |
| * `total_length_of_fwd_packets` | |
| * `total_length_of_bwd_packets` | |
| * `down_up_ratio` | |
| #### Packet size statistics | |
| * `packet_length_min`, `packet_length_max` | |
| * `packet_length_mean`, `packet_length_std`, `packet_length_variance` | |
| * Forward and backward packet length metrics | |
| #### Timing & inter-arrival times | |
| * `flow_duration` | |
| * `flow_iat_mean`, `flow_iat_std`, `flow_iat_max`, `flow_iat_min` | |
| * Forward and backward IAT statistics | |
| * `active_*`, `idle_*` features | |
| #### Rate-based features | |
| * `flow_bytes_per_s` | |
| * `flow_packets_per_s` | |
| * `fwd_packets_per_s`, `bwd_packets_per_s` | |
| #### TCP flag counters | |
| * `syn_flag_count`, `ack_flag_count`, `rst_flag_count` | |
| * `fin_flag_count`, `psh_flag_count`, `urg_flag_count` | |
| * `cwr_flag_count`, `ece_flag_count` | |
| #### Bulk and subflow statistics | |
| * `*_bulk_*` features | |
| * `subflow_fwd_*`, `subflow_bwd_*` | |
| > **Note:** Some CICFlowMeter features are conditionally emitted. | |
| > Missing or undefined numeric values were **filled with `0.0`**, which semantically indicates *absence of that behavior*. | |
| --- | |
| ### 2. Semantic Flags (`semantic_flags`) | |
| Each flow includes deterministic, interpretable indicators derived from numeric features: | |
| | Flag | Meaning | | |
| | --------------------- | --------------------------------------------------------- | | |
| | `high_packet_rate` | Extremely high packets per second | | |
| | `one_way_traffic` | Forward-only traffic (no backward response) | | |
| | `syn_ack_imbalance` | Large SYN/ACK imbalance | | |
| | `uniform_packet_size` | Low packet size variance | | |
| | `long_idle_c2` | Long idle periods (possible command-and-control behavior) | | |
| These flags are: | |
| * Deterministic | |
| * Stable across dataset versions | |
| * Suitable for rule-based IDS and hybrid systems | |
| --- | |
| ## Preprocessing Summary | |
| The dataset was generated using a **fully deterministic preprocessing pipeline**: | |
| * Column name normalization | |
| * Conversion of `NaN` / `±Infinity` → `0.0` | |
| * Explicit label normalization | |
| * No row removal due to missing numeric values | |
| * Stratified train/validation/test splits | |
| * Explicit Hugging Face feature schemas | |
| No rebalancing, oversampling, or augmentation was applied. | |
| --- | |
| ## Class Imbalance | |
| The dataset is **highly imbalanced**, with benign traffic dominating. | |
| This reflects **real-world network conditions** and is intentional. | |
| Users are encouraged to: | |
| * Use **precision, recall, F1, PR-AUC** | |
| * Apply **class weighting** or cost-sensitive learning | |
| * Avoid relying on accuracy alone | |
| --- |