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Stefan Eder, thank you for posting this paper. Its is an important read and formalises the issues that we have been working to resolve with cybersecurity adoption of AI. Specifically, autonomous agent deployment and operation within a closed world vs. when AI is required to operate in real-world autonomous and hostile situations. Requiring a rethink in AI model testing.
As the paper points out, AI models operate well in controlled, structured, and well-defined situations where model accuracy against a human baseline is severe. Where misinformation can throw models off track, affecting reasoning and outcomes.
The authors argue that AI development and models need to prioritise adversarial robustness, a capability that is addressed better in domain-specific models that are grounded on ‘transparent and verifiable ground truth’. A method that provides guide rails to combat agents guessing and attempting trial-and-error, something that you don’t want when you are operating in a cybersecurity or cyber audit domain.
@Parava Security Solutions
#aicyber #domainspecificai
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