IoT Manufacturer: ZKP and IoT Device Firmware Integration (zk-Device Design)

In this page, we will review the solutions to integrate the FidesInnova ZKP tools with an existing IoT device.

Solution 1: C++ Library

The FidesInnova C++ Library offers a proof generation function specifically designed for IoT firmware developers. This function can be seamlessly integrated into IoT firmware to generate proofs whenever necessary.

The IoT developer should insert their program file into the FidesInnova Commitment Generator. This tool creates a new file to be compiled and uploaded to the IoT devices and a Commitment to be uploaded to the blockchain.

Hardware implementation of C++ library using ESP32-C6:

• Microcontroller: ESP32-C6

• Processor Architecture: RV32IMAC

• Program storage space: 400KB

• Dynamic memory: 20KB

• Clock Speed: 160MHz

Average result time:

• Commitment generation time in C++: 0.5~1 sec

• ZKP generation time in C++: 0.5~1.5 sec

• Verification time in C++: 0.5~1 sec

To integrate with new hardware, we need the following information:

• Microcontroller

• Processor Architecture

• Clock Speed (MHz)

• RAM (SRAM) Size

• Flash Memory

• Hardware Cryptographic Support

• Random Number Generation (RNG)

• Hardware Cryptographic Support

• Cryptography Libraries

GitHub

https://github.com/FidesInnova/zk_iot_c

To access the GitHub, please email [e-mail]

Solution 2: Rust Crates

Similar to the C++ library, FidesInnova's Rust Crates offer a proof generation function for Rust programs. This functionality allows developers to seamlessly integrate proof generation into their Rust applications, ensuring robust and secure performance.

GitHub

https://github.com/FidesInnova/zk_iot_rust

To access the GitHub, please email [e-mail]

Solution 3: FidesInnova ZKP Mini Board

Using a JTAG connection, the ZKP Mini Board connects to the IoT board and extracts the register values of the device's processor during firmware execution. This process enables real-time monitoring and verification of firmware behavior.

The extracted register values are used to generate zero-knowledge proofs (ZKPs), providing verifiable evidence of the firmware's integrity without disclosing sensitive information. These ZKPs are then made available for the IoT device to use.