Context-Aware Data Access Control for Secure Support Cases
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Solution Overview
Problem
Conventional data management systems face challenges in providing efficient customer assistance while ensuring user privacy and security, as customer assistance agents often have unrestricted access to user data, leading to potential misuse and trust issues.
Innovation Solution
Implementing a system that monitors user activity and generates support cases with defined data access rules, using machine learning to refine access requests and restrict data access to only what is necessary for assistance, ensuring secure and efficient customer support.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If customer assistance agents are granted access to user data to resolve problems, then assistance effectiveness is improved, but data security and privacy are compromised
Solution Approach 1:
The patent segments user data access by creating distinct data categories (accessible data, restricted data, confidential data) and assigning different access levels to assistance agents based on their role and the specific support case requirements. This allows agents to access only the minimum necessary data to resolve user issues while maintaining security for other data portions.
Solution Approach 2:
The patent implements local quality by making data access rights specific to each assistance agent, support case type, and data category rather than applying uniform access rules. Access permissions are tailored locally to match the specific needs of each assistance scenario while maintaining overall security posture.
2Reliability
If unrestricted data access is provided to assistance agents, then problem resolution capability is improved, but trust and security posture deteriorate
Solution Approach 1:
The patent implements dynamic data access control where assistance agents' data access permissions are not static but change based on the specific support case context, user consent preferences, and the nature of the issue being resolved. Access rights are dynamically adjusted to provide sufficient information for problem resolution while maintaining security and user trust.
Solution Approach 2:
The patent introduces an intermediary layer (the data access control system) that mediates between the assistance agents' need for information and the user's data security requirements. This intermediary selectively filters and provides data based on predefined policies, agent credentials, and case requirements, enabling problem resolution without compromising security or trust.
3Productivity
If all user data is made accessible to assistance agents, then assistance completeness is improved, but resource usage and security exposure increase
Solution Approach 1:
The patent extracts and isolates only the specific data elements necessary for resolving each support case from the broader user data set. By extracting precisely the needed information rather than providing comprehensive access, the system maintains assistance completeness while reducing computing resource usage and security exposure associated with handling unnecessary data.
Data Source
AI summary
A method and system monitors activity of a user of a data management system and detects a trigger event in the activity of the user. The method and system generates a support case responsive to the trigger event. The support case includes support rules defining what types of the user's personal data will be accessible to an assistance agent when the user requests assistance related to the trigger event. The method and system utilizes machine learning processes to determine what types of user related data should be accessible to assistance agents in support cases.