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configs:
- config_name: alert_triaging_tii
data_files:
- split: tp
path: data/alert_triaging_tii_tp.jsonl
- split: fp
path: data/alert_triaging_tii_fp.jsonl
- config_name: alert_triaging_cic
data_files:
- split: test
path: data/alert_triaging_cic_test.jsonl
- config_name: sia_dataset
data_files:
- split: test
path: data/sia_dataset_test.jsonl
license: apache-2.0
task_categories:
- question-answering
language:
- en
tags:
- cybersecurity
- incident-analysis
- LLM-benchmark
pretty_name: SIABench
---
task_categories:
- question-answering
language:
- en
tags:
- cybersecurity
- incident-analysis
- LLM-benchmark
---
# SIABench — Security Incident Analysis Benchmark
SIABench is a benchmark for evaluating LLMs on cybersecurity incident analysis tasks, developed at **Concordia University's Security Research Centre** in collaboration with **Defence Research and Development Canada (DRDC)**.
## Dataset Structure
SIABENCH contains three sub-datasets accessible as separate configs:
| Config | Description | Splits |
|---|---|---|
| `alert_triaging_tii` | 100 alert triaging scenarios (TII-SSRC-23 source) | `tp` (50), `fp` (50) |
| `alert_triaging_cic` | Alert triaging scenarios (CIC source) | `tp`, `fp` |
| `sia_dataset` | 25 open-ended CTF forensics scenarios | `train` |
## Loading the Dataset
```python
from datasets import load_dataset
# Load alert triaging (TII)
tii = load_dataset("SIABench/SIA_Dataset", "alert_triaging_tii")
# Load alert triaging (CIC)
cic = load_dataset("SIABench/SIA_Dataset", "alert_triaging_cic")
# Load CTF investigation scenarios
sia = load_dataset("SIABench/SIA_Dataset", "sia_dataset")
```
## Scenario Structure
Each JSON file contains two blocks:
**1. `metadata`** — scenario identification
- `scenario_name`: unique ID
- `alert_type` (TII/CIC only): `"True"` (TP) or `"False"` (FP)
**2. `sia_components`** — the LLM task
- `scenario`: natural language description of the incident
- `tools_available`: CLI tools the LLM agent can invoke
- `files_available`: linked PCAP file (`capture.pcap`)
- `directory`: set to `"(directory_of_the_file)"`
- `questions`: Q&A pairs (with `adversarial_tactic` in SIA_Dataset) |