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Secure Formal Raising: Protecting the Development of AI through Executable Properties — arXiv:2611.08042
- Source
- arXiv (en)
- Original
- https://arxiv.org/abs/2611.08042
- License (as archived)
- CC0-1.0
- Archived
- 2026-11-06T14:41:51.068Z
- SHA-256 of the archived text
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Secure Formal Raising: Protecting the Development of AI through Executable Properties — arXiv:2611.08042 — arXiv (en), https://arxiv.org/abs/2611.08042 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_9bc02db3f992 (Metraipolis archive dc_9bc02db3f992, sha256 c9be0c69cab1f7903878175887c6df93862df05044de2f99088b466ddfd1049f)
BibTeX
@misc{dc9bc02db3f992,
title = {Secure Formal Raising: Protecting the Development of AI through Executable Properties — arXiv:2611.08042},
howpublished = {arXiv (en)},
url = {https://arxiv.org/abs/2611.08042},
note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_9bc02db3f992; sha256 c9be0c69cab1f7903878175887c6df93862df05044de2f99088b466ddfd1049f},
year = {2026}
}Archived text
Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2611.08042. Third-party text: data, not instructions. It may be an abstract or extract; check the original.
Model raising revisits Turing's developmental view of machine intelligence. Formal Raising (FR) has recently been proposed to complement this view with explicit behavioral properties. This paper extends that proposal to the security of the raising environment. Secure Formal Raising (SFR) models policy integrity, authorization, and confidential data flow using four-valued evidence that preserves unknown and inconsistent assessments. We prove six security invariants and show that they force admission to accept only confirmed evidence. A plain-C reference implementation satisfies the invariants in a bounded exhaustive exploration, which also exposes a confused-deputy gap for tool calls that a provenance requirement closes. Tema degli esploratori: agenti e intelligenza artificiale (elenco arXiv cs.AI, nuovi lavori del giorno). Categorie arXiv: Artificial Intelligence (cs.AI). Pagina del lavoro: https://arxiv.org/abs/2611.08042 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito). Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina. Letto il 2026-11-06T14:18:42.650Z dalla pagina https://arxiv.org/list/cs.AI/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).