NLP Service Control Mapping for External Systems
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Solution Overview
Problem
Organizations face challenges in determining and enforcing appropriate service controls for external services, as they often lack direct control over these external systems.
Innovation Solution
A system utilizing natural language processing (NLP) to extract and analyze service control requirements from documents associated with external services, generating encoded representations of service controls, determining similarity scores, and identifying representative service controls for categories of external services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If organizations use external services to expand functionality and reduce operational burden, then service versatility and ease of operation improve, but control over service security and privacy deteriorates
Solution Approach 1:
The patent introduces an intermediary system that acts as a mediator between the organization and external service providers. This intermediary automatically generates service control requirements by analyzing service descriptions and matching them with security frameworks, thereby restoring organizational control over external services without requiring direct management of the service infrastructure.
Solution Approach 2:
The system performs preliminary actions by proactively generating service control requirements before services are deployed or used. It analyzes service descriptions in advance, identifies potential security and privacy risks, and establishes control requirements upfront, rather than reacting to issues after they occur.
2Measurement precision
If organizations manually determine service controls for external services, then control precision improves, but time consumption and operational complexity increase
Solution Approach 1:
The patent replaces the manual mechanical process of determining service controls with an automated computational system. The system uses natural language processing to analyze service descriptions and automatically generates control requirements, eliminating the need for manual review and significantly reducing the time required while maintaining or improving accuracy through systematic analysis.
Solution Approach 2:
The system enables self-service by allowing service control requirements to be automatically generated based on service descriptions provided by external providers. The organization does not need to manually determine controls for each service; instead, the system autonomously analyzes and generates appropriate control requirements, reducing operational burden.
3Reliability
If organizations implement comprehensive service controls for all external services, then security and privacy protection improve, but system complexity and implementation difficulty increase
Solution Approach 1:
The patent applies segmentation by breaking down the complex task of determining service controls into manageable components. It processes each service independently by analyzing its description, identifying relevant security and privacy concerns, and generating specific control requirements for that service. This modular approach reduces overall system complexity while maintaining comprehensive coverage.
Solution Approach 2:
The system achieves universality by using a unified framework that can handle multiple types of external services with different functionality and risk profiles. It applies the same automated analysis process across diverse services, generating appropriate control requirements for each without requiring separate manual processes, thereby reducing implementation complexity while maintaining comprehensive security coverage.
Data Source
AI summary
A system determines service controls for organizations. The system receives documents from external systems representing reports storing information describing service controls for external services. The service controls are represented using natural language text. The system encodes the service controls using a natural language model to generate encoded service controls. The system determines similarity scores for pairs of service controls. The system determines one or more representative service controls for a category of external services based on similarity scores of pairs of the service controls. The system stores a mapping from categories of external services to representative service controls determined from the set of service controls corresponding to the category of external services. The system uses the mapping for determining representative service controls for external services corresponding to a set of services used by an organization.