IoT Gateway Smart Contract Access Control
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Solution Overview
Problem
Existing manufacturing systems lack effective decentralized trust mechanisms to prevent fraud and detect defects in IoT devices, leading to potential cyber incidents and production disruptions.
Innovation Solution
Implementing a distributed ledger system with a proof-of-eligibility consensus algorithm and token-based two-steps access control, coupled with a Deep Convolutional Generative Adversarial Network (DCGAN) for inline quality control and defect detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a distributed ledger system with consensus algorithm is implemented, then decentralized trust and fraud prevention are improved, but device complexity and system overhead increase
Solution Approach 1:
The patent introduces a smart contract as an intermediary layer between the distributed ledger and IoT devices. The smart contract automatically executes access control logic and fraud detection rules, mediating between the complex blockchain consensus mechanism and simple IoT device operations. This allows the system to maintain decentralized trust while shielding devices from direct exposure to blockchain complexity.
Solution Approach 2:
The system segments functionality into distinct layers: the distributed ledger handles trust and consensus, smart contracts handle access control logic, IoT gateways handle device communication, and individual IoT devices handle local operations. This segmentation allows each component to be optimized independently, reducing overall system complexity while maintaining decentralized trust.
2Reliability
If token-based access control is implemented, then security against unauthorized access is improved, but processing time and operational complexity increase
Solution Approach 1:
The system performs preliminary actions by pre-generating and caching access tokens with embedded permissions and validity periods. IoT devices can present these pre-approved tokens for rapid authentication without requiring real-time consensus validation for each access request. This preliminary token issuance maintains security while dramatically reducing authorization processing time during actual operations.
Solution Approach 2:
Access tokens are designed with periodic validity, automatically expiring after a predetermined time period. This periodic renewal mechanism ensures security is maintained through regular re-authentication while allowing rapid access during valid periods. The system periodically refreshes tokens rather than requiring continuous validation, balancing security with operational efficiency.
3Manufacturing precision
If DCGAN model is deployed for defect detection, then manufacturing precision and quality control are improved, but computational requirements and energy consumption increase
Solution Approach 1:
The DCGAN (Deep Convolutional Generative Adversarial Network) model creates a digital copy or virtual representation of normal product features during training. During defect detection, the system compares actual product data against this learned digital copy rather than requiring complex real-time analysis. This copying approach enables high-precision defect detection while reducing computational energy consumption by using pattern matching against pre-learned normal states.
4Reliability
If distributed ledger technology is implemented across multiple IoT devices, then trust and security are improved, but communication overhead and network traffic increase
Solution Approach 1:
The system extracts and separates critical trust-related data (access tokens, authentication credentials, fraud detection records) from general operational data. Only these extracted essential trust elements are transmitted across the distributed ledger network, while routine operational data remains local to individual devices. This extraction approach maintains decentralized trust for critical operations while minimizing communication overhead and energy consumption for overall system operation.
Data Source
AI summary
Embodiments couple a corresponding IoT gateway to each IoT device, each IoT gateway monitoring for operation events of a smart contract of a distributed ledger, each IoT device and IoT gateway coupled to the distributed ledger. In response to a client initiating an operation of a first IoT device, embodiments generate a corresponding event by the smart contract and transmit an authorization request to an authorization system and in response receive an access token corresponding to the operation. Embodiments transmit the access token to one or more of the IoT gateways, each IoT gateway monitoring for the event and determining whether it corresponds to the first IoT device and then implementing the operation at the first IoT device. Embodiments determine a defect in any of the IoT devices using a trained Deep Convolutional Generative Adversarial Network (“DCGAN”) model coupled to the distributed ledger.