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Everything you wanted to know about AI Security but were afraid to ask

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The Artificial Intelligence Risk Management Framework (AI RMF) by NIST

When engaging with AI and AI-based solutions, it's important to understand AI's limitations, risks and vulnerabilities. The Artificial Intelligence Risk Management Framework (AI RMF) by NIST is a set of guidelines and best practices designed to help organizations identify, assess and manage the risks associated with the deployment and use of artificial intelligence technologies.

The framework consists of six elements:

1. Valid and Reliable - AI can provide the wrong information, which is also known in GenAI as "hallucinations". It's important that companies can validate the AI they're adopting is accurate and reliable.
2. Safe - Ensuring that the prompted information isn't shared with other users, like in the infamous Samsung case.
3. Secure and Resilient - Attackers are using AI for cyber attacks. Organizations should ensure the AI system is protected and safe from attacks and can successfully thwart attempts to exploit it or use it for assisting with attacks.
4. Accountable and Transparent - It's important to be able to explain the AI supply chain and to ensure there is an open conversation about how it works. AI is not magic.
5. Privacy-enhanced - Ensuring the prompted information is protected and anonymized in the data lake and when used.
6. Fair - This is one of the most important elements. It means managing harmful bias. For example, there is often bias in AI facial recognition, with light-skinned males being more accurately identified compared to women and darker skin colors. When using AI for law enforcement, for example, this could have severe implications.

Additional resources for managing AI risk include the MITRE ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems), OWASP Top 10 for ML and Google's Secure AI Framework (SAIF).

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See the full article here: https://thehackernews.com/2023/09/everything-you-wanted-to-know-about-ai.html