Gene Cloud Genomic Data Encryption and Access Control
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Solution Overview
Problem
The handling of genomic data poses challenges in ensuring authenticity, privacy, and security, particularly with the transition from traditional genetic tests to Whole Genome Sequencing, where data can be stored indefinitely and used for future tests, raising concerns about patient consent and the potential for unintended revelation of genetic information with far-reaching consequences.
Innovation Solution
A system called Gene Cloud is introduced, which includes secure storage and processing of genomic data, ensuring privacy through encryption and anonymous handling, utilizing a distributed trust model, certification for healthcare use, and standardized programming tools, along with a marketplace for intellectual property, to facilitate trusted and secure handling of genomic information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Whole Genome Sequencing is implemented to enable comprehensive genetic analysis, then diagnostic capability and medical insight are improved, but data security risks and privacy concerns worsen
Solution Approach 1:
The patent segments genomic data into multiple encrypted partitions and distributes them across different storage locations. No single location contains the complete unencrypted genome, thereby reducing the impact of potential security breaches while maintaining full diagnostic capability through authorized reassembly.
Solution Approach 2:
The patent introduces trusted intermediaries (such as certified authorities and encrypted processing environments) that mediate between the genomic data and users. These intermediaries verify authenticity, enforce access controls, and ensure that data is only accessed according to authorized purposes, thus protecting privacy while enabling medical analysis.
2Adaptability or versatility
If genomic data is stored indefinitely for future testing, then adaptability and future diagnostic potential are improved, but vulnerability to unauthorized access and misuse worsen
Solution Approach 1:
The patent implements dynamic access controls where permissions, encryption keys, and authorization levels can change over time. Data storage policies are not static but adapt to evolving security requirements, regulatory changes, and user preferences, allowing long-term storage while maintaining flexible protection mechanisms.
Solution Approach 2:
The patent applies preliminary security measures including encryption, authentication mechanisms, and access policy establishment before data is stored. These pre-configured protections ensure that even if data is stored indefinitely, unauthorized access is prevented from the outset, and future access can be controlled through pre-established frameworks.
3Reliability
If digital signatures and authentication mechanisms are implemented, then data authenticity and trustworthiness are improved, but system complexity worsen
Solution Approach 1:
The patent implements universal authentication mechanisms and standardized digital signature protocols that can be applied across different genomic data types, processing platforms, and user systems. This multi-functional approach ensures authenticity verification without requiring separate complex systems for each application, thereby reducing overall system complexity while maintaining high reliability.
Data Source
AI summary
Trusted, privacy-protected systems and methods are disclosed for processing, handling, and performing tests on human genomic and other information. According to some embodiments, a system is disclosed that is a cloud-based system for the trusted storage and analysis of genetic and other information. Some embodiments of the system may include or support some or all of authenticated and certified data sources; authenticated and certified diagnostic tests; and policy-based access to data.