IoT Telemetry Sharing via NFTs for Privacy-Preserving Recommendations
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Solution Overview
Problem
Existing IoT systems face challenges in securely transmitting telemetry data to authorized third parties while ensuring data integrity and user privacy, and determining device-specific recommendations.
Innovation Solution
The system utilizes Non-Fungible Tokens (NFTs) minted by IoT device manufacturers, linking device and user identifiers, with smart contracts defining data transmission criteria, enabling secure and real-time data transfer to third parties via a bridge protocol and machine learning models for user-specific recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If IoT telemetry data is transmitted to third parties, then data utilization and recommendations are improved, but user privacy and data security are compromised
Solution Approach 1:
The patent introduces NFTs as intermediary tokens that mediate between IoT devices and third parties. These NFTs contain cryptographic proofs and device identifiers without exposing raw user data, enabling third parties to verify device authenticity and receive telemetry data while user identity remains protected. The NFT acts as a trustless intermediary that facilitates data sharing without direct exposure of sensitive user information.
Solution Approach 2:
The patent transforms user identity protection from a binary state (exposed/hidden) to a cryptographic parameter space. By using cryptographic proofs, hashed identifiers, and token-based authentication, the system changes the parameter of identity representation from plaintext user data to mathematical proofs that verify authenticity without revealing underlying identities. This allows data utilization while maintaining privacy through parameter transformation.
2Speed
If real-time telemetry data transmission is implemented, then system responsiveness and recommendation accuracy are improved, but network bandwidth and system complexity increase
Solution Approach 1:
The patent implements preliminary actions by pre-minting NFTs with embedded device identifiers, cryptographic proofs, and access permissions before data transmission occurs. These NFTs are stored in distributed ledgers in advance, so when real-time telemetry data needs to be transmitted, the authentication and authorization framework is already in place. This eliminates the need for complex real-time authentication negotiations, reducing system complexity while maintaining fast data transmission.
Solution Approach 2:
The patent uses cryptographic copying mechanisms where NFTs contain replicated device identifiers and authentication proofs that can be verified by multiple third parties simultaneously. Instead of creating complex point-to-point authentication channels for each data transmission, the system creates cryptographic copies of device identity proofs in NFT format that can be independently verified, reducing the complexity of real-time authentication infrastructure.
3Reliability
If third parties access IoT device identifiers, then data verification and trust are improved, but user anonymity and privacy protection are reduced
Solution Approach 1:
The patent segments device identification information into multiple cryptographic components stored within NFTs. Instead of containing the full device identifier in plaintext, the NFT stores segmented cryptographic proofs, hashed portions of identifiers, and zero-knowledge proof components. This segmentation allows third parties to verify device authenticity through cryptographic validation while the complete device identifier and user identity remain segmented and hidden, maintaining both verification reliability and user anonymity.
Solution Approach 2:
The patent replaces mechanical/exposure-based verification systems with cryptographic verification mechanisms. Instead of third parties directly accessing and viewing device identifiers through traditional authentication channels, the system substitutes this with cryptographic proof verification using NFTs. Third parties verify device authenticity through mathematical proofs and cryptographic signatures embedded in NFTs, eliminating the need for direct exposure of device identifiers and user information.
Data Source
AI summary
Real-time transmission of IoT telemetry data to a third-party and use of such data by the third-party for purposes of determining IoT device-related recommendations specific to the IoT device user. Machine learning models receive the IoT telemetry data, as a least a part of the inputs, to determine recommendations that are tied to the IoT device and specific to the IoT device user. Non Fungible Tokens (NFTs) are minted by the IoT device manufacturer/distributor and hold a link to an IoT device identifier and an IoT device user identifier and include a smart contract formed between the third-party and the IoT device user that defines the criteria for the telemetry data that is to be acquired by the third-party. Use of the NFT allows for IoT gateways/data listeners to determine which IoT telemetry data is to be transmitted to the third-party and allows for the transmission to occur without identifying the IoT user in the transmissions.