title: Building Trust: Foundations of Security, Safety and Transparency in AI
summary: This paper explores the rapidly evolving ecosystem of publicly available AI
  models, and their potential implications on the security and safety landscape.
  As AI models become increasingly prevalent, understanding their potential risks
  and vulnerabilities is crucial. We review the current security and safety
  scenarios while highlighting challenges such as tracking issues, remediation,
  and the apparent absence of AI model lifecycle and ownership processes.
  Comprehensive strategies to enhance security and safety for both model
  developers and end-users are proposed. This paper aims to provide some of the
  foundational pieces for more standardized security, safety, and transparency in
  the development and operation of AI models and the larger open ecosystems and
  communities forming around them.
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paper_authors.name: Huzaifa Sidhpurwala
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paper_authors.fullname: Huzaifa Sidhpurwala
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paper_authors.name: Garth Mollett
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paper_authors.fullname: Garth Mollett
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paper_authors.name: Emily Fox
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paper_authors.fullname: Emily Fox
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paper_authors.user: TheMoxieFox
paper_authors._id: 673d461ca2f8aff91ef34195
paper_authors.name: Mark Bestavros
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paper_authors.fullname: Mark Bestavros
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paper_authors._id: 673d461ca2f8aff91ef34196
paper_authors.name: Huamin Chen
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paper_authors.fullname: Huamin Chen
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paper_authors.user: HuaminChen
paper_title: Building Trust: Foundations of Security, Safety and Transparency in AI
paper_summary: This paper explores the rapidly evolving ecosystem of publicly available AI
  models, and their potential implications on the security and safety landscape.
  As AI models become increasingly prevalent, understanding their potential risks
  and vulnerabilities is crucial. We review the current security and safety
  scenarios while highlighting challenges such as tracking issues, remediation,
  and the apparent absence of AI model lifecycle and ownership processes.
  Comprehensive strategies to enhance security and safety for both model
  developers and end-users are proposed. This paper aims to provide some of the
  foundational pieces for more standardized security, safety, and transparency in
  the development and operation of AI models and the larger open ecosystems and
  communities forming around them.