PQC Threat Mapping for Quantum-Resistant Data Protection
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Solution Overview
Problem
Existing data protection systems are vulnerable to quantum computing threats, particularly from quantum computers that can decrypt traditionally secure data, and there is a need for a systematic approach to transition to quantum-resistant cryptography while anticipating future decryption vulnerabilities.
Innovation Solution
The integration of a Post Quantum Cryptography (PQC) modeler and a Harvest Now Decrypt Later (HNDL) modeler to systematically select quantum-resistant algorithms, model cybersecurity threats, and map these algorithms with threats to reduce the threat vector surface, ensuring secure data migration and protection against future quantum decryption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional cryptographic algorithms are used, then current data protection requirements are met, but vulnerability to quantum computing threats increases
Solution Approach 1:
The system performs preliminary action by proactively migrating from traditional cryptographic algorithms to post-quantum cryptographic algorithms before quantum computers can actually decrypt the data. The PQC modeler identifies and implements quantum-resistant algorithms in advance, and the HNDL modeler detects potential future decryption vulnerabilities, allowing the system to prepare defensive measures before the threat materializes.
Solution Approach 2:
The system applies parameter changes by transitioning cryptographic algorithms based on their resistance parameters to quantum attacks. The mapping system correlates protection algorithms with cybersecurity threats using alignment techniques, selecting algorithms with parameters that provide quantum resistance while maintaining current security requirements.
2Object-affected harmful factors
If post-quantum cryptographic algorithms are implemented, then quantum resistance is achieved, but system complexity increases
Solution Approach 1:
The system applies self-service by using automated modelers and mapping systems that independently perform cryptographic algorithm selection, threat modeling, and migration planning. The PQC modeler automatically determines appropriate post-quantum algorithms, the HNDL modeler autonomously models threats, and the mapping system self-configures the correlations, reducing the need for manual cryptographic management despite increased system complexity.
Solution Approach 2:
The system achieves universality by creating a multi-functional framework where the mapping system serves multiple purposes: correlating protection algorithms with threats, generating migration plans, updating validation statuses, and reducing threat vector surfaces. This unified approach manages cryptographic complexity through a single versatile system rather than separate specialized components.
3Reliability
If comprehensive threat modeling is performed, then cybersecurity risk is reduced, but processing time increases
Solution Approach 1:
The system implements feedback by continuously updating workstream element validation statuses based on mapping results and threat modeling outcomes. The mapping system correlates protection algorithms with cybersecurity threats and uses this feedback to refine migration plans and adjust validation states, creating an iterative process that improves security assessment efficiency over time while maintaining comprehensive threat coverage.
Data Source
AI summary
Systems, methods, and computer-readable storage media for data protection. One system includes a data processing system including memory and one or more processors configured to determine one or more protection algorithms corresponding to one or more workstream elements of a workstream of one or more data systems. The processors are further configured to model one or more cybersecurity threats of the one or more data systems. The processors are further configured to map the one or more workstream elements of the workstream into the one or more cybersecurity threats based on one or more correlations between the one or more protection algorithms and the one or more cybersecurity threats. The processors are further configured to update a workstream element validation status of the one or more workstream elements based on the mapping of the one or more workstream elements.