Policy Arbitration Server Ranking Service Policies
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing policy arbitration methods either force privacy information holders to agree to service policies without flexibility or require inefficient multiple interactions between privacy information holders and users to reach agreement, limiting the ability to customize services based on data quality and increasing interaction burden.
Innovation Solution
A policy arbitration method that generates a ranking of service policies based on divergence from user policies, allowing privacy information holders to select a service policy that aligns with their preferences, reducing the number of interactions needed for agreement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If policy arbitration requires multiple interactions between privacy information holders and users to reach agreement, then policy agreement flexibility is improved, but interaction burden and time consumption increase
Solution Approach 1:
The server pre-ranks service policies based on their divergence from the user policy before the arbitration process begins. This preliminary ranking action eliminates the need for multiple iterative interactions, as the privacy information holder can directly select from pre-sorted options, thereby reducing interaction time while maintaining policy agreement flexibility
Solution Approach 2:
The system provides feedback by presenting the ranked list of service policies to the privacy information holder, allowing them to select the most suitable policy based on their preferences. This feedback mechanism enables efficient arbitration without requiring multiple back-and-forth interactions, resolving the contradiction between flexibility and time consumption
2Quantity of substance
If service policies are presented without ranking, then completeness of policy options is improved, but ease of operation deteriorates due to increased selection burden
Solution Approach 1:
The service policies are segmented and organized into a ranked list based on their divergence from the user policy. This segmentation presents the complete set of policies while organizing them by relevance, making it easier for privacy information holders to select appropriate policies without reviewing every option equally, thus improving ease of operation while maintaining completeness
3Productivity
If policy arbitration forces agreement without flexibility, then arbitration efficiency is improved, but adaptability to user preferences deteriorates
Solution Approach 1:
The system dynamically ranks service policies based on their divergence from the specific user policy provided by the privacy information holder. This dynamic ranking mechanism maintains arbitration efficiency by automating the sorting process while adapting to individual user preferences, allowing the system to efficiently present policies tailored to each user's specific requirements rather than using a static fixed-order list
Data Source
AI summary
A policy arbitration method comprises: entering a user policy in which a privacy information holder describes at least one rule that is a pair of a data type of privacy information possessed by the privacy information holder and the way to handle the data type; generating, using the user policy and a service policy set that includes at least one service policy in which a privacy information user describes at least one rule that is a pair of a data type of the privacy information and the way to handle the data type, a ranking of the service policy according to the degree of divergence between the user policy and the service policy; and displaying the service policy ranking on a privacy information holder terminal.