Multi-Tier Data Security Auditing for Tokenized Sensitive Data
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Solution Overview
Problem
Existing data security systems, including tokenization and encryption, are vulnerable to cyberattacks and malicious activities that seek unauthorized access to sensitive data, particularly in multi-tiered enclaves, leading to potential data breaches and identity theft.
Innovation Solution
A multi-tiered security system that tokenizes sensitive data using random number arrays across different enclaves and audits the tokenized data, allowing authorized users to decode sensitive data in plaintext while ensuring unauthorized access is restricted, and enabling the permanent deletion of improperly retained data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional tokenization or encryption is used to secure sensitive data, then data protection is improved, but the system becomes vulnerable to cyberattacks and unauthorized access
Solution Approach 1:
The patent divides the security system into multiple tiers (first security enclave, second security enclave, third security enclave) with progressively stronger security measures. Each tier handles specific security functions, and data must pass through multiple layers of verification and encryption, making it resistant to single-point failures and cyberattacks that target individual encryption layers.
Solution Approach 2:
The patent implements nested security enclaves where the first security enclave contains tokenized data, which is then wrapped in the second security enclave with additional encryption, and finally nested within the third security enclave with enhanced protection. This nested structure ensures that compromising one layer does not expose the data, as each layer provides an additional barrier.
2Object-affected harmful factors
If multi-tiered security enclaves are implemented, then security against cyberattacks is improved, but system complexity increases
Solution Approach 1:
The patent introduces a security auditor as an intermediary component that mediates between the different security enclaves and external systems. The auditor verifies data classification, manages access requests, and coordinates security protocols across tiers, simplifying the overall system architecture by providing a centralized coordination mechanism rather than requiring direct complex interactions between all components.
Solution Approach 2:
The patent dynamically adjusts security parameters based on data sensitivity and access requests. The system can modify encryption strength, access control levels, and verification requirements according to the specific data being handled and the authorized user's clearance level, allowing the system to maintain high security without consistently operating at maximum complexity.
3Reliability
If data is tokenized and distributed across multiple enclaves, then data security is improved, but data accessibility and retrieval become more difficult
Solution Approach 1:
The patent implements a feedback mechanism where the security auditor receives requests for data access, verifies the user's authorization level, and dynamically determines which enclaves can be accessed. This feedback loop ensures that authorized users can efficiently retrieve data through a streamlined process, while unauthorized access is automatically blocked, maintaining both security and ease of operation for legitimate users.
Solution Approach 2:
The system performs preliminary actions by pre-tokenizing and classifying data before it enters the multi-tiered enclave system. Data is pre-processed and assigned to appropriate security levels in advance, so when access is needed, the system can quickly retrieve and verify the data without requiring complex real-time processing, thus maintaining ease of access while preserving security.
4Productivity
If automated data classification is used, then data management efficiency is improved, but misclassification of sensitive data may occur
Solution Approach 1:
The security auditor receives feedback from automated classification systems and manually reviews borderline or high-sensitivity data to correct misclassifications. This feedback loop allows the system to maintain high automated processing efficiency while ensuring accuracy through human verification of critical data, preventing misclassification from compromising security.
Solution Approach 2:
The system performs preliminary automated classification to efficiently sort the majority of data into appropriate security enclaves. However, for data that falls into uncertain categories or requires enhanced verification, the system preliminarily flags it for manual review by the security auditor, ensuring that potential misclassifications are caught and corrected before final data placement.
Data Source
AI summary
Methods and systems disclosed herein describe tokenizing potentially sensitive data fields and distributing the tokenized data across various enclaves associated with multi-tiered security levels. A user may request to unmask the tokenized data. By auditing the tokenized data and the various enclaves, an authorized user may determine that the tokenized data has been properly classified or improperly misclassified. After confirming the classification of the tokenized data, the data may be decoded and provided in plaintext in its appropriate enclave or permanently deleted from all corresponding enclaves.