Blockchain Authentication Using Merkle Proofs for Physical Access
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Solution Overview
Problem
Existing authentication methods, particularly physical authentication, face challenges with security risks, operational burdens, and inefficiencies due to the need for centralized data management and manual data entry, while traditional NLP methods for novelty detection are computationally expensive and lack adaptability.
Innovation Solution
Utilize blockchain technology with Merkle Trees and cryptographic keys for secure, efficient user authentication, and a graph-based approach for novelty detection in NLP, leveraging QR codes and mobile applications for user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If physical authentication mechanisms (ID cards, biometric devices) are used, then user identification can be achieved, but security risks and operational burdens increase due to centralized data management
Solution Approach 1:
The system segments authentication data into distributed blockchain nodes rather than centralized storage. Each user's authentication credentials are divided into cryptographic components stored across the decentralized network, eliminating single-point security risks and reducing centralized management complexity.
Solution Approach 2:
The patent introduces Merkle Trees as an intermediary data structure between users and the blockchain network. The Merkle Root serves as a mediator that enables efficient verification of user credentials without requiring direct access to individual user data, reducing both security risks and operational complexity.
2Measurement precision
If traditional autoencoder methods are used for novelty detection, then anomaly detection capability is achieved, but computational expense and training time increase significantly
Solution Approach 1:
The system extracts only the essential features needed for novelty detection from the complex autoencoder architecture. By using Merkle Tree hash comparisons and cryptographic verification, the patent removes unnecessary computational layers while retaining the core anomaly detection capability, significantly reducing energy consumption.
Solution Approach 2:
The patent changes the detection parameters from continuous neural network outputs to discrete cryptographic hash comparisons. This parameter transformation enables novelty detection through deterministic hash matching rather than probabilistic neural network inference, reducing computational expense while maintaining detection accuracy.
3Reliability
If Merkle Trees are updated each time a user is added, then data integrity is maintained, but update frequency and processing load increase
Solution Approach 1:
The system performs preliminary hashing of user credentials before adding them to the Merkle Tree. By pre-computing hash values and preparing authentication data in advance, the patent reduces the computational load during actual Merkle Tree updates, maintaining data integrity while improving update efficiency.
Data Source
AI summary
System and methods for physical authentication using blockchain technologies. A user list is encoded via hashes of respective wallet addresses to construct a Merkle Tree. The Merkle Root of the constructed Merkle Tree is recorded on the blockchain. The Merkle Tree and the Merkle Root are updated each time a user is added to the organization. A user is authenticated by submitting a message to the client, which creates a Merkle Proof and sends it to the blockchain for authentication. The process can be facilitated by a mobile application that generates a Quick Response (QR) code representing the user's wallet address.