Encryption as a Service with Anomaly Detection
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Solution Overview
Problem
Existing Encryption-as-a-Service (EaaS) architectures face challenges in maintaining optimal data security due to increased complexity and costs with multiple external systems, as they often require proprietary cryptographic algorithms and keys, and lack comprehensive security measures beyond encryption services.
Innovation Solution
The implementation of an enterprise framework that utilizes artificial intelligence (AI) and machine learning (ML) for request classification, anomaly detection, intelligent key management, and data isolation to enhance EaaS, allowing for secure, scalable, and vendor-agnostic cryptographic operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If each external computer system uses its own cryptographic algorithm and keys, then data security is maintained for each system, but system complexity and maintenance cost increase
Solution Approach 1:
The patent implements a universal cryptographic service that can handle multiple external systems through a single interface. The service accepts encryption requests from any external system, automatically manages algorithm selection and key generation, and returns encrypted data without requiring each system to implement its own cryptographic stack. This multi-functional approach maintains data security across diverse systems while centralizing complexity management.
Solution Approach 2:
The patent introduces an intermediary cryptographic service layer between external systems and the encryption operations. This mediator handles all cryptographic complexities including algorithm selection, key management, and encryption/decryption operations. External systems interact only with the simplified service interface, while the intermediary manages the complexity of supporting multiple algorithms and keys, thus reducing overall system complexity.
2Adaptability or versatility
If multiple encryption services are provided for different external systems, then each system's specific cryptographic requirements are met, but maintenance cost increases
Solution Approach 1:
The cryptographic service is designed as a universal platform that supports multiple encryption algorithms (AES, RSA, DES) and key management mechanisms through a single unified service. The service automatically detects the required algorithm based on the external system's credentials and applies the appropriate cryptographic operations. This eliminates the need to maintain separate encryption services for each algorithm, significantly reducing maintenance costs while preserving adaptability to different cryptographic requirements.
Solution Approach 2:
The service implements dynamic parameter configuration where cryptographic algorithms, key lengths, and security parameters can be changed centrally without modifying the service architecture. The system stores configuration parameters for each external system and automatically applies the correct parameters during encryption operations. This allows the service to adapt to different cryptographic requirements while maintaining a single, easily maintainable codebase.
3Ease of operation
If cryptographic service is provided as standalone solution, then implementation is simplified, but comprehensive data security is compromised
Solution Approach 1:
The patent merges multiple security functions into a single integrated cryptographic service: authentication of external systems, algorithm selection, key generation and management, encryption/decryption operations, and security anomaly detection. This unified approach maintains implementation simplicity while providing comprehensive data security through coordinated execution of multiple security mechanisms within one service framework.
Solution Approach 2:
The service implements feedback mechanisms where each encryption request is analyzed against historical patterns and security policies. The system monitors for anomalies in encryption requests, key usage patterns, and system behavior, and can dynamically adjust security parameters or reject suspicious operations. This feedback loop enhances comprehensive security while maintaining the simplicity of the standalone service architecture.
Data Source
AI summary
A system and method mediate transfer of encrypted data files between local applications and external computer systems. Application containers perform cryptographic operations using stored credentials to decrypt data coming from these external systems and configurably forward them to the local applications, and to encrypt data sent from the local applications to the external systems. Access to this encryption-as-a-service (EaaS) functionality is gated by a fingerprint service that classifies requests by security level, and detects anomalous requests. Security classification is performed by a supervised machine learning algorithm, while anomalous request detection is performed by unsupervised machine learning algorithm. Stored keys are monitored, and when they near expiration or are damaged, embodiments proactively undertake key renewal and key exchange with the external computer systems. Containerization enables key storage in multiple vaults, thereby making such storage vendor-agnostic.