Hybrid Cryptography Configuration for AI-Guided Secure Migration
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Solution Overview
Problem
Existing cryptographic techniques in networks are difficult to modify or migrate without impacting surrounding infrastructure due to non-standardized configurations and lack of automated configuration techniques, and they may not be optimized for hardware capabilities or Quality of Service (QoS) requirements.
Innovation Solution
Utilizing AI/ML techniques to analyze and refine cryptographic configurations by generating a cryptographic ontology, identifying potential modifications, and optimizing cryptography techniques based on hardware capabilities and QoS requirements, while ensuring compatibility and performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cryptographic techniques are modified or migrated, then security can be improved, but it impacts surrounding infrastructure and requires laborious manual configuration
Solution Approach 1:
The system performs self-service by automatically analyzing its own cryptographic configurations, identifying vulnerabilities, and generating remediation plans without requiring manual security expert intervention. The AI/ML models autonomously evaluate cryptographic ontologies and produce optimization recommendations.
Solution Approach 2:
Manual cryptographic analysis and configuration processes are replaced with AI/ML-based automated systems. The mechanical process of security experts manually reviewing cryptographic settings is substituted with intelligent algorithms that automatically detect vulnerabilities and suggest improvements.
2Reliability
If stronger cryptographic techniques are implemented, then security is improved, but hardware resource consumption increases
Solution Approach 1:
The system dynamically adjusts cryptographic parameters such as key lengths, algorithm types, and encryption strength based on hardware capability assessments. AI/ML models analyze the relationship between cryptographic strength and resource consumption, optimizing parameters to achieve adequate security with minimal resource usage.
Solution Approach 2:
Different cryptographic techniques are applied to different parts of the system based on local hardware capabilities and security requirements. Rather than uniformly applying strong cryptography everywhere, the system tailors cryptographic strength to match local resource constraints while maintaining overall security.
3Ease of operation
If cryptographic configurations are standardized, then ease of migration is improved, but adaptability to specific hardware capabilities and QoS requirements decreases
Solution Approach 1:
The cryptographic configuration system is dynamic rather than static. AI/ML models continuously adapt cryptographic settings based on changing hardware capabilities, QoS requirements, and security threats. The system can dynamically adjust configurations during operation to optimize for different conditions.
Solution Approach 2:
The cryptographic configuration is segmented into multiple independent components that can be individually optimized. The system divides cryptographic settings into separate configurable elements (algorithms, key lengths, modes) that can be independently adjusted based on specific hardware capabilities and requirements.
4Reliability
If manual cryptographic analysis is performed, then security vulnerabilities can be identified, but time and expert resources are consumed
Solution Approach 1:
Manual cryptographic analysis by security experts is replaced with AI/ML-based automated analysis systems. The time-consuming mechanical process of expert review is substituted with intelligent algorithms that can rapidly evaluate cryptographic configurations and identify vulnerabilities.
Solution Approach 2:
AI/ML models serve as intermediaries between cryptographic configurations and security assessment. Rather than direct manual analysis, the system introduces intelligent intermediary layers that automatically evaluate configurations, identify vulnerabilities, and generate remediation recommendations.
Data Source
AI summary
A device described herein may maintain a set of models that include a plurality of cryptography configurations. A particular cryptography configuration may specify a first cryptography technique, a second cryptography technique, and a combination scheme. The device may provide the particular cryptography configuration to a particular system. The particular system may generate a first key based on the first cryptography technique, generate a second key based on the second cryptography technique, and generate a third key based on the first key, the second key, and the combination scheme. The third key may be used to encrypt communications associated with the particular system, such as by using the third key as a symmetric key.


