# A Cybersecurity Risk Analysis Framework for Systems with Artificial Intelligence Components

arXiv: https://arxiv.org/abs/2401.01630 · HTML: https://mlsanity.com/paper/2401.01630/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Jan 2024.

## Built on by (most cited first, 3 of 3)

- [Reward Hacking and Agent Containment Failure: A Monte Carlo Study Based on the 2026 Hugging Face Incident](https://mlsanity.com/paper/2609.32390/) (2026)
- [Standardized Threat Taxonomy for AI Security, Governance, and Regulatory Compliance](https://mlsanity.com/paper/2511.21901/) (2025)
- [A Knowledge-Based Multi-Agent Framework for Security Control Recommendation](https://mlsanity.com/paper/2607.09954/) (2026)

## Abstract (arXiv)

The introduction of the European Union Artificial Intelligence Act, the NIST Artificial Intelligence Risk Management Framework, and related norms demands a better understanding and implementation of novel risk analysis approaches to evaluate systems with Artificial Intelligence components. This paper provides a cybersecurity risk analysis framework that can help assessing such systems. We use an illustrative example concerning automated driving systems.