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NIST scientist proves AI unassailable with conventional security models

By PulseAugur Editorial · [1 sources] ·

A senior scientist at NIST has published a mathematical proof, building on Kurt Gödel's work, demonstrating that AI systems cannot be made completely unassailable using conventional security models. The proof suggests that inherent limitations exist in rendering AI systems fully secure. AI

IMPACT Suggests fundamental limitations in securing AI systems, potentially impacting future development and deployment strategies.

RANK_REASON The cluster discusses a peer-reviewed journal publication and a mathematical proof related to AI security. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Mastodon — sigmoid.social →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

NIST scientist proves AI unassailable with conventional security models

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11 / 100
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The cluster discusses a peer-reviewed journal publication and a mathematical proof related to AI security. [lever_c_demoted from research: ic=1 ai=1.0]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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safety, paper
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High
Clearly on-topic for AI-industry coverage.
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Breaking (< 6h)
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COVERAGE [1]

  1. Mastodon — sigmoid.social TIER_1 English(EN) · [email protected] ·

    Don't blame AI, blame Kurt Goedel "Try as we might, we can never render AI completely unassailable using conventional security models. In the peer-reviewed jour

    Don't blame AI, blame Kurt Goedel "Try as we might, we can never render AI completely unassailable using conventional security models. In the peer-reviewed journal IEEE Security and Privacy, Apostol Vassilev, a senior scientist at the National Institute of Standards and Technolog…

    LINKS nist.gov/…/nist-mathematical-proof-suppor…

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