Private Cloud Compute

lastmod 2025-11-09created 2025-11-091 edits

A new frontier for AI privacy in the cloud

Introducing Private Cloud Compute

Apple Intelligence is a personal intelligence system that brings powerful generative models to iPhone, iPad, and Mac.
Private Cloud Compute (PCC) is a cloud intelligence system for complex data processing that strengthens the security of user data.
PCC extends Apple's device security and privacy into the cloud, ensuring that user data is not accessible to anyone, including Apple.

Stateless computation on personal user data: PCC uses data only to fulfill the user's request and does not retain it after processing.
Enforceable guarantees: PCC does not rely on external components and can technically enforce all of its security and privacy guarantees.
No privileged runtime access: PCC is designed so that Apple staff cannot bypass privacy guarantees through privileged access.
Non-targetability: Designed so that attackers cannot target a specific user's data.
Verifiable transparency: Lets security researchers verify PCC's security and privacy guarantees.

Root of trust: PCC nodes bring Apple silicon and security technologies into the data center to strengthen security.
Hardware and operating system: Uses a new operating system built on the security technologies of iOS and macOS.
Cloud extensions: Excludes remote shells and system introspection tools, and provides only a limited set of operational metrics.

User data processing: PCC uses data only to fulfill the user's request and deletes it after processing.
Security technologies: Uses Secure Boot, Code Signing, Secure Enclave, and more to ensure data integrity.

No remote shells or debugging tools: PCC nodes do not include remote shells or debugging tools.
Observability and management tools: Only tools designed not to expose user data are used.

Hardware security: Strengthens hardware security from the manufacturing stage all the way to the data center.
Target diffusion: Request metadata does not include personally identifiable information.

Publishing software images: All PCC software images are published for security research.
Transparency log: All code measurements are recorded in a cryptographic transparency log and made public.
Research environment: Provides tools and images so security researchers can verify PCC software.

Stronger security: PCC strengthens the security of user data and sets a new standard for cloud AI processing.
Transparency: Publishing software images so security researchers can verify them increases trustworthiness.
Technical challenges: Solves technical challenges such as stateless computation and no privileged runtime access.
Competing products: Worth comparing with other cloud security solutions such as Google's Confidential Computing.
Adoption considerations: Initial setup and maintenance costs should be considered when adopting PCC.

author Zer0 sitemap