Artificial intelligence is moving beyond software applications towards controlling physical equipment, creating new cybersecurity challenges for businesses using automated systems.
Anthropic’s Model Hardware Standard (MHS), currently in research preview, aims to help AI agents discover, understand and operate equipment through a common interface. Potential applications include robotic arms, microscopes, laboratory equipment and manufacturing systems.
However, allowing AI to control machinery raises questions about whether the equipment receiving instructions can be trusted. Even if an AI agent is authorised to issue a command, the receiving device could be cloned, replaced or compromised.
Device Authority argues that security must cover both the AI agent and the physical machine. Device identity, authentication and authorisation can help establish whether equipment is genuine and whether an operation should be permitted.
The reliability of data is another concern. AI systems may use information received from connected devices to make decisions and adjust subsequent actions. If the source of that information cannot be verified, the resulting decisions may also be unreliable.
Device Authority identifies hardware-based device identity, attestation and policy-based access controls as potential ways to address these risks. Its Dynamic Device Key Generation technology is designed to establish device identity and help detect cloned or substituted endpoints.
As AI takes on more responsibility for operating physical equipment, verifying the identity and security status of connected machines could become an increasingly important part of protecting industrial and other connected environments.
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