Data Lifecycle Discovery Platform for Multi-Jurisdiction Compliance
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Solution Overview
Problem
Conventional techniques for data communication, exchange, storage, and display are deficient in protecting sensitive and personal data, inefficient in implementation, and lack robustness, leading to unauthorized access and exposure of such data, and are limited in scope, failing to comply with legal and contractual requirements.
Innovation Solution
A data lifecycle discovery platform (DLDP) that employs artificial intelligence and machine learning to identify, manage, and secure data across multiple tenants and languages, ensuring compliance with legal and contractual obligations through a modular, scalable design, utilizing containerized applications and a rules engine to enforce data protection policies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional data communication and storage techniques are used, then data can be exchanged and stored across networks, but data security and protection against unauthorized access are insufficient
Solution Approach 1:
The patent segments data into multiple shards distributed across different storage locations. Each shard alone is insufficient to reconstruct the original data, providing inherent security against unauthorized access. The data lifecycle discovery platform tracks and manages these segmented data pieces, ensuring that even if some shards are compromised, the complete data remains protected.
Solution Approach 2:
The patent introduces an intermediary data lifecycle discovery platform that acts as a mediator between data storage systems and access requests. This platform discovers, tracks, and manages data locations and access policies, providing an additional layer of security control and monitoring that prevents unauthorized access while allowing legitimate data exchange.
2Reliability
If data is stored in multiple locations for security, then data protection improves, but system complexity and management difficulty increase
Solution Approach 1:
The data lifecycle discovery platform is designed as a universal system that performs multiple functions: discovering data locations, tracking data movement, managing access policies, and monitoring data lifecycle events. This multi-functional approach consolidates what would otherwise be separate complex systems into a single unified platform, reducing overall system complexity while maintaining data stored in multiple locations for security.
3Ease of manufacture
If conventional data management approaches are used, then implementation is simple, but compliance with legal and contractual requirements is insufficient
Solution Approach 1:
The patent implements dynamic data lifecycle management where the system automatically adapts its behavior based on data sensitivity, jurisdiction, and applicable laws. The data lifecycle discovery platform continuously discovers and updates information about data locations and access requirements, dynamically adjusting management policies to maintain compliance without requiring complex manual configuration for each legal requirement.
4Ease of operation
If data is communicated globally across networks, then data accessibility improves, but risk of data exposure and breach increases
Solution Approach 1:
The patent applies local quality by implementing location-specific and context-specific security measures. The data lifecycle discovery platform identifies where data is stored and what local security requirements apply, then applies appropriate protection measures tailored to each location and data type. This allows global data accessibility while maintaining localized security controls that reduce exposure risk in each specific context.
Data Source
AI summary
Techniques for data lifecycle discovery and management are presented. Data lifecycle discovery platform (DLDP) can identify data of users, data type, and language of data stored in data stores (DSs) of entities based on scanning of data from databases. DLDP determines compliance of DLDP and DSs with obligations relating to data protection arising out of jurisdictional laws or agreements. DLDP generates rules to facilitate complying with and enforcing laws and agreements. DLDP can determine, and present to authorized users, risk scores relating to levels of compliance of the DLDP, associated platforms, or entities, risk indicator metrics, or a privacy health index of the organization associated with DLDP. DLDP can manage user rights regarding data, and access to data in DSs and information relating thereto stored in secure data store of DLDP. DLDP can remediate issues involving anomalies indicating non-compliance. DLDP can utilize machine learning to enhance various functions of DLDP.