# SecQA: A Concise Question-Answering Dataset for Computer Security

## Overview

SecQA is a specialized dataset created for the evaluation of Large Language Models (LLMs) in the domain of computer security. It consists of multiple-choice questions aimed at assessing the understanding and application of LLMs' knowledge in computer security.

## Dataset Description

SecQA is an innovative dataset designed to benchmark the performance of Large Language Models (LLMs) in the field of computer security. It contains a series of multiple-choice questions generated by GPT-4, based on the content from the textbook [Computer Systems Security: Planning for Success](https://web.njit.edu/~rt494/security/).

The dataset is structured into two versions:
- **SecQA v1**: Foundational level questions
- **SecQA v2**: More advanced questions with higher difficulty

This design allows for a preliminary evaluation of LLMs across different levels of complexity in understanding and applying computer security principles.

## Dataset Structure

Each question in the dataset offers four answer choices, with only one being the correct answer. To ensure fairness and eliminate any bias in question design, the answer choices have been carefully shuffled.

## Example Questions

### Sample Question 1

**Question**: What is the purpose of implementing a Guest Wireless Network in a corporate environment?

**Options**:
- A: To provide unrestricted access to company resources
- B: To replace the primary corporate wireless network
- C: To bypass network security protocols
- D: To offer a separate, secure network for visitors

**Answer**: D

**Explanation**: A Guest Wireless Network provides visitors with internet access while segregating them from the main corporate network, enhancing security by preventing unauthorized access to sensitive company resources.

### Sample Question 2

**Question**: What is a typical indicator that an Intrusion Detection System (IDS) or Intrusion Prevention System (IPS) might identify as a network attack?

**Options**:
- A: Anomalies or strange behaviors in network traffic
- B: Unauthorized software installation
- C: Frequent system reboots
- D: Regular updates to firewall rules

**Answer**: A

**Explanation**: IDS/IPS systems monitor network traffic and can identify network attacks by detecting anomalies, strange behaviors, or known exploit signatures in the traffic.
## Uses

The primary application of SecQA is to serve as a benchmark for testing and evaluating the capabilities of LLMs in the domain of computer security.

### Direct Use

The SecQA dataset is primarily intended for evaluating and benchmarking the performance of Large Language Models (LLMs) in understanding and applying principles of computer security. It's suitable for:

- Academic research
- Development of AI in cybersecurity education
- Testing the ability of models to interpret and respond to security-related scenarios

### Out-of-Scope Use

SecQA is not designed for and should not be used as:
- A sole resource for real-world cybersecurity decision-making or incident response
- Training models for unethical purposes, such as hacking or creating security exploits
- A comprehensive resource for all aspects of computer security

## Citation

```bibtex
@article{liu2023secqa,
  title={SecQA: A Concise Question-Answering Dataset for Evaluating Large Language Models in Computer Security},
  author={Liu, Zefang},
  journal={arXiv preprint arXiv:2312.15838},
  year={2023}
}
```

## Resources

- **Repository**: [SecQA on Hugging Face](https://huggingface.co/datasets/zefang-liu/secqa)
- **Paper**: [SecQA: A Concise Question-Answering Dataset for Evaluating Large Language Models in Computer Security](https://arxiv.org/abs/2312.15838)
- **Author**: [Zefang Liu](https://www.linkedin.com/in/zefang-liu/)