Add canonical CIC-IDS-2017 parquet (flowprep) + dataset card

README.md

@@ -2,4 +2,236 @@
 license: other
 license_name: cic-ids-2017-research-use
 license_link: https://www.unb.ca/cic/datasets/ids-2017.html
+pretty_name: CIC-IDS-2017 — Canonical NetFlow (flowprep)
+language:
+  - en
+task_categories:
+  - tabular-classification
+tags:
+  - network-security
+  - cybersecurity
+  - netflow
+  - flow
+  - intrusion-detection
+  - nids
+  - canonical-schema
+  - flowprep
+  - deeptempo
+size_categories:
+  - 100K<n<1M
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: data/cic-ids-2017-canonical.parquet
+dataset_info:
+  config_name: default
+  features:
+    - name: timestamp
+      dtype: int64
+    - name: src_ip
+      dtype: string
+    - name: dest_ip
+      dtype: string
+    - name: src_port
+      dtype: int32
+    - name: dest_port
+      dtype: int32
+    - name: fwd_bytes
+      dtype: int64
+    - name: bwd_bytes
+      dtype: int64
+    - name: fwd_pkts
+      dtype: int64
+    - name: bwd_pkts
+      dtype: int64
+    - name: flow_dur
+      dtype: float64
+    - name: protocol
+      dtype: int32
+    - name: attack
+      dtype: string
+    - name: label
+      dtype: string
+  splits:
+    - name: train
+      num_examples: 101094
 ---
+
+# CIC-IDS-2017 — Canonical NetFlow (flowprep)
+
+A ~101k-row slice of the **CIC-IDS-2017** intrusion-detection dataset, normalized
+into a single clean, typed, unit-normalized **canonical NetFlow** parquet table by
+[**flowprep**](https://github.com/DeepTempo/flowprep) — the open-source flow
+canonicalization tool DeepTempo runs in production ahead of inference.
+
+This is a **conversion proof-point**: it shows what a real, messy research dataset
+looks like after `flowprep canonicalize` resolves its vendor column names, infers
+its units, and types its columns. The output is ordinary parquet —
+`pandas`/`polars`/`DuckDB`/Spark read it natively, **the file format is the API**.
+
+> ⚠️ This is a **small demonstration slice**, not the full CIC-IDS-2017 dataset.
+> For research, obtain the complete dataset from
+> [UNB CIC](https://www.unb.ca/cic/datasets/ids-2017.html) and cite accordingly
+> (see [Citation](#citation)).
+
+## Why this exists
+
+Every network-ML project and SOC pipeline starts by solving the same unglamorous
+problem: flow data arrives with different column names, duration units, and
+timestamp encodings. The same field is `src_ip`, `Source IP`, `srcaddr`, or
+`ipv4_src_addr`; a duration might be seconds, ms, µs, or ns with nothing telling
+you which. flowprep maps 100+ column spellings onto one canonical schema and
+normalizes units, so labeled research data stays labeled and is ready to train on
+immediately. This dataset is that step, done once, published.
+
+## How it was produced
+
+Fully reproducible from the sample bundled in the flowprep repo (no network access
+required):
+
+```bash
+git clone https://github.com/DeepTempo/flowprep
+cd flowprep
+cargo build --release
+
+# aliased CIC columns (total_fwd_pkts, datetime timestamps) -> canonical schema
+./target/release/flowprep canonicalize \
+    examples/cic2017_sample.parquet \
+    cic-ids-2017-canonical.parquet
+# -> Wrote 101094 flows
+```
+
+`flowprep` resolved the source's CIC-style aliases (e.g. `total_fwd_pkts` →
+`fwd_pkts`, `total_bwd_pkts` → `bwd_pkts`), converted the typed-datetime
+`timestamp` to int64 epoch microseconds, kept `flow_dur` in float64 seconds, and
+passed the ground-truth label columns through unchanged. The alias map is not
+hard-coded — it is loaded at compile time from flowprep's declarative
+[`schemas/netflow/v1/schema.json`](https://github.com/DeepTempo/flowprep/blob/main/schemas/netflow/v1/schema.json),
+the same artifact DeepTempo's production ingestion uses. Output is single-row-group
+ZSTD-compressed parquet.
+
+## Schema
+
+| field | type | unit / encoding | description |
+|---|---|---|---|
+| `timestamp` | int64 | epoch **microseconds** | flow start time |
+| `src_ip` | string | | source IP |
+| `dest_ip` | string | | destination IP |
+| `src_port` | int32 | | source L4 port |
+| `dest_port` | int32 | | destination L4 port |
+| `fwd_bytes` | int64 | bytes | source→destination bytes |
+| `bwd_bytes` | int64 | bytes | destination→source bytes |
+| `fwd_pkts` | int64 | packets | source→destination packets |
+| `bwd_pkts` | int64 | packets | destination→source packets |
+| `flow_dur` | float64 | **seconds** | flow duration |
+| `protocol` | int32 | IANA number | **null in this slice** — the CIC sample carries no protocol field; kept for canonical-schema fidelity |
+| `attack` | string | `benign` / `attack` | ground-truth label (string) |
+| `label` | string | `0` / `1` | ground-truth label (binary, string-encoded) |
+
+`attack` and `label` are two encodings of the same binary ground truth and are
+preserved exactly as flowprep emitted them (label passthrough). This slice does
+**not** carry per-attack subtype labels (DoS, PortScan, …).
+
+## Statistics
+
+- **Rows:** 101,094 flows
+- **Class balance:** 81,171 benign (80.29%) / 19,923 attack (19.71%)
+- **Unique source IPs:** 4,656 · **unique destination IPs:** 7,254
+- **Timestamp range (as stored, passed through from source):** 2017-03-07 →
+  2017-07-07 UTC. CIC-IDS-2017 was captured over a work week in July 2017; the
+  exact values here are the source sample's timestamps, unchanged by flowprep.
+- **`flow_dur`:** 0 – 120.0 s (mean 14.84 s)
+- **`fwd_bytes`:** 0 – 1,034,689 (mean 527) · **`bwd_bytes`:** 0 – 538,000,000 (mean 16,097)
+- **`fwd_pkts`:** 1 – 180,725 (mean 9.4) · **`bwd_pkts`:** 0 – 242,974 (mean 10.5)
+- **File:** `data/cic-ids-2017-canonical.parquet` (~1.7 MB, ZSTD, single row group)
+
+## Usage
+
+```python
+import pandas as pd
+df = pd.read_parquet("hf://datasets/<org>/cic-ids-2017-flowprep/data/cic-ids-2017-canonical.parquet")
+# that's the whole integration — no bindings, no client library
+
+# binary label for training/eval
+y = (df["label"] == "1").astype(int)
+```
+
+```python
+# or with the datasets library
+from datasets import load_dataset
+ds = load_dataset("<org>/cic-ids-2017-flowprep", split="train")
+```
+
+```python
+import duckdb
+duckdb.sql("SELECT attack, count(*) FROM 'data/cic-ids-2017-canonical.parquet' GROUP BY attack")
+```
+
+## Intended use
+
+- A small, clean, **labeled** flow table for prototyping NIDS / flow-classification
+  models and for **reproducible evaluation** (the canonical schema removes
+  preprocessing variance — a documented source of up to ~40% metric swing across
+  NIDS papers).
+- A worked example of canonical NetFlow for the new generation of **network
+  foundation models**, which expect one stable, unit-normalized schema.
+- A reference for what flowprep output looks like before you point it at your own
+  pcap / nfdump / OCSF / CSV sources.
+
+## Limitations & honest notes
+
+- **Not the full dataset.** A ~101k-flow demonstration slice; not class-complete
+  and not a substitute for the official CIC-IDS-2017 release.
+- **Binary labels only.** `attack`/`label` are benign-vs-attack; no per-attack
+  subtype is present in this slice.
+- **`protocol` is null** (the source sample has no protocol field); the column is
+  retained only for canonical-schema fidelity.
+- **Timestamps are passed through** from the source unchanged; treat them as
+  relative ordering, not authoritative wall-clock capture times.
+- **Known CIC-IDS-2017 caveats apply.** The original dataset has documented
+  labeling and generation issues discussed in the literature; do not treat results
+  on this slice as production detection performance.
+
+## License & attribution
+
+The **canonical parquet artifact and this dataset card** are released by DeepTempo;
+the **flowprep tool** that produced it is [Apache-2.0](https://github.com/DeepTempo/flowprep/blob/main/LICENSE).
+
+The underlying flow data **derives from CIC-IDS-2017**, © Canadian Institute for
+Cybersecurity (CIC), University of New Brunswick. It is redistributed here as a
+small conversion example, **with attribution and citation as required by CIC**. For
+research use, obtain the full dataset from
+[UNB CIC](https://www.unb.ca/cic/datasets/ids-2017.html) and cite the paper below.
+If you are a rights holder and have concerns about this slice, please open an issue
+on the [flowprep repo](https://github.com/DeepTempo/flowprep).
+
+## Citation
+
+If you use this data, cite the original CIC-IDS-2017 paper:
+
+```bibtex
+@inproceedings{sharafaldin2018toward,
+  title     = {Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characterization},
+  author    = {Sharafaldin, Iman and Lashkari, Arash Habibi and Ghorbani, Ali A.},
+  booktitle = {Proceedings of the 4th International Conference on Information Systems Security and Privacy (ICISSP)},
+  year      = {2018}
+}
+```
+
+And, optionally, the tool used to canonicalize it:
+
+```bibtex
+@software{flowprep,
+  title  = {flowprep: network telemetry to ML-ready canonical NetFlow parquet},
+  author = {DeepTempo},
+  url    = {https://github.com/DeepTempo/flowprep},
+  year   = {2026}
+}
+```
+
+## Acknowledgments
+
+- **Canonical Institute for Cybersecurity (UNB)** for CIC-IDS-2017.
+- Built with [**flowprep**](https://github.com/DeepTempo/flowprep) by
+  [DeepTempo](https://deeptempo.ai).

data/cic-ids-2017-canonical.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:25160b9a5a7b72ebe36775b834cf2d646a00a02b16fcdda33c6796c16c864b1f
+size 1740286

make_dataset.sh

@@ -0,0 +1,25 @@
+#!/usr/bin/env bash
+# Reproduce the canonical CIC-IDS-2017 parquet from the flowprep example slice.
+# No network access required. Run from anywhere; paths are resolved relative to
+# this script and the flowprep repo at ../../../oss/flowprep.
+set -euo pipefail
+cd "$(dirname "$0")"
+
+FLOWPREP_DIR="../../../oss/flowprep"
+BIN="$FLOWPREP_DIR/target/release/flowprep"
+SRC="$FLOWPREP_DIR/examples/cic2017_sample.parquet"
+OUT="data/cic-ids-2017-canonical.parquet"
+
+if [[ ! -x "$BIN" ]]; then
+  echo "Building flowprep release binary..."
+  ( cd "$FLOWPREP_DIR" && cargo build --release )
+fi
+
+mkdir -p data
+echo "=== canonicalize CIC-IDS-2017 sample -> canonical schema ==="
+"$BIN" canonicalize "$SRC" "$OUT"
+echo
+echo "=== preview ==="
+"$BIN" peek "$OUT" -n 5
+echo
+echo "Wrote $OUT"