Blockchain Credential Authentication With Behavioral Anomaly Checks
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Solution Overview
Problem
Centralized identity management systems are vulnerable to security threats, acting as single points of failure and posing risks for unauthorized access, necessitating a more robust and decentralized authentication solution.
Innovation Solution
A decentralized authentication system using a distributed blockchain network with a peer-to-peer network of nodes and AI/ML algorithms to validate user credentials, storing hashed credentials immutably and monitoring behavioral patterns to prevent unauthorized access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a centralized identity management system is used for user credential authentication, then the authentication process is simplified and centralized control is achieved, but the system becomes a single-point of failure and vulnerable to security threats
Solution Approach 1:
The patent divides the centralized authentication system into multiple distributed nodes forming a blockchain network. Each node stores a copy of the authentication data and can independently validate credentials, eliminating the single-point-of-failure vulnerability while maintaining authentication functionality across the distributed system.
Solution Approach 2:
The patent introduces an AI/ML-based authentication monitoring system as an intermediary layer between users and the blockchain network. This monitoring system analyzes behavioral patterns, detects anomalies, and dynamically adjusts authentication requirements, thereby enhancing security without significantly complicating the user authentication process.
2Reliability
If hashed user credentials are stored on a distributed blockchain network with majority consensus mechanism, then security is enhanced and single-point of failure is eliminated, but the system complexity increases
Solution Approach 1:
The patent implements a multi-functional authentication system where the blockchain network simultaneously provides secure credential storage, distributed validation, and immutable audit logging. The AI monitoring system performs behavioral analysis, anomaly detection, and dynamic authentication policy enforcement, consolidating multiple security functions into integrated components that reduce overall system complexity despite the distributed architecture.
3Reliability
If AI/ML monitoring system analyzes behavioral patterns in real-time to detect suspicious activity, then unauthorized access is prevented, but processing time and computational resources increase
Solution Approach 1:
The patent implements preliminary action by pre-training the AI/ML models on historical authentication data and behavioral patterns before deployment. The system continuously learns from authenticated users' behavioral patterns during normal operations, building robust models that can quickly detect anomalies. This pre-training and continuous learning approach enables the system to perform real-time behavioral analysis with minimal processing delay, as the models are already optimized for rapid pattern recognition.
Data Source
AI summary
A method for user credential authentication includes receiving real-time logs from a blockchain network that is configured to perform an authentication process of a user. The real-time logs are normalized and bucketized to generate processed real-time logs, which are stored in a block and are added to a blockchain. The processed real-time logs are analyzed to identify the plurality of real-time behavioral patterns of the user. A first authentication score is determined by comparing a first real-time behavioral pattern to a respective first historical behavioral pattern. The first authentication score is compared to a first authentication score threshold, which corresponds to the first real-time behavioral pattern and the respective first historical behavioral pattern. In response to the first authentication score being less than the first authentication score threshold, a first instruction is sent to the blockchain network to temporarily stop the authentication process of the user.