Delegated Signing via Sensitivity Classification
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Solution Overview
Problem
Existing document management systems struggle to securely distribute sensitive documents between entities while preventing unauthorized access, especially when substituting receiving entities are involved.
Innovation Solution
A centralized document system that determines the sensitivity level of documents using a machine-learned model combining document and entity attributes, and applies policies to decide whether to delegate sensitive documents, thereby preventing unauthorized access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the system distributes sensitive documents to substitute receiving entities, then document execution can proceed when the original recipient is unavailable, but sensitive information security is compromised
Solution Approach 1:
The centralized document system acts as an intermediary between the originating entity and substitute receiving entities. It receives delegation requests, evaluates sensitivity using machine-learned models, checks organizational policies, and makes the final decision on whether to permit distribution. This intermediary role resolves the contradiction by introducing a security gatekeeper that enables document execution only when safe.
Solution Approach 2:
The system performs preliminary sensitivity analysis and policy evaluation before distributing documents to substitute recipients. By applying machine-learned models to assess document sensitivity and checking organizational policies in advance, the system prevents sensitive information exposure before it can occur, while still allowing legitimate document execution to proceed.
2Object-affected harmful factors
If the system scans each document for sensitive information, then sensitive documents can be identified and protected, but processing resources are consumed significantly
Solution Approach 1:
The system changes the parameter of sensitivity analysis from a universal scan of all documents to a selective analysis based on document attributes and distribution context. By using machine-learned models that evaluate multiple parameters (document type, recipient role, organizational policy, delegation necessity), the system achieves high detection accuracy only when needed, significantly reducing processing resource consumption.
3Measurement precision
If the system applies machine-learned models to all documents, then sensitivity detection accuracy is maximized, but processing time increases
Solution Approach 1:
The system applies partial action by using machine-learned models selectively rather than universally. It applies the models only to documents that meet certain criteria (e.g., when delegation is involved, when document attributes suggest potential sensitivity). This partial application maintains high detection accuracy for relevant cases while minimizing processing time for the overall document flow.
4Adaptability or versatility
If the system permits delegation to substitute receiving entities, then document execution flexibility is improved, but unauthorized access risk increases
Solution Approach 1:
The system implements feedback mechanisms by continuously evaluating delegation requests against organizational policies, document sensitivity levels, and recipient authorization status. The machine-learned models provide feedback on the risk level of each delegation request, and the system adjusts its decisions based on this feedback. This creates a dynamic security system that maintains flexibility while preventing unauthorized access through continuous monitoring and evaluation.
Data Source
AI summary
A centralized document system generates a document package in response to a request by an originating entity. The document package includes at least one document for execution by a first receiving entity. The first receiving entity can specify a set of permissions for a second receiving entity to perform actions to documents within the package on behalf of the first receiving entity. Accordingly, the system may provide the document package to both the first and second receiving entities for the first receiving entity to execute the at least one document. Before providing the document to the second receiving entity, system may determine whether there is a sensitive document in the package and whether to delegate the document to the second entity. Accordingly, the system may prevent a sensitive document package from being provided to the second receiving entity for execution.