Automatic Privacy Level Detection for Electronic Device Data Protection
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Solution Overview
Problem
Existing electronic devices lack effective automatic data protection mechanisms, leading to potential information leakage when users forget to configure privacy permissions, as current methods rely on active user configuration and do not differentiate data protection based on sensitivity levels.
Innovation Solution
An electronic device method that automatically determines the privacy level of data based on its semantic meaning and context, using a privacy level identification model, to select appropriate presentation and storage manners, ensuring differential protection and security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If privacy permission is configured for specific information, then data security is improved, but user operation complexity increases and users may forget to configure permissions
Solution Approach 1:
The system automatically identifies and classifies data by privacy level without requiring user configuration. The electronic device autonomously performs data sensitivity assessment and applies appropriate protection measures, eliminating the need for users to manually configure privacy permissions for each data item.
Solution Approach 2:
The manual configuration process is replaced with an automated intelligent system that uses algorithms to identify and classify data. The system substitutes user action with automated data analysis and classification mechanisms that continuously monitor and protect data without user intervention.
2Reliability
If all data is protected with the same high security level, then data security is improved, but access convenience deteriorates
Solution Approach 1:
Different protection measures are applied to different data items based on their classified privacy levels. High-sensitivity data receives stronger protection while low-sensitivity data has easier access, creating localized quality variations in security measures across the data set rather than uniform protection.
Solution Approach 2:
The system changes security parameters dynamically based on data classification results. Different privacy levels correspond to different security parameters such as authentication requirements, encryption strength, and access control policies, allowing the system to adapt protection intensity to data sensitivity.
3Reliability
If automatic privacy level determination is implemented, then data protection effectiveness is improved, but system complexity increases
Solution Approach 1:
The system segments data into distinct privacy levels (first privacy level, second privacy level, etc.) based on sensitivity. This segmentation allows the complex protection mechanism to be divided into manageable categories, where each category has predefined protection rules, reducing overall system complexity through structured classification.
Data Source
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AI summary
Embodiments of this application provide a data protection method and an electronic device, and relate to the field of electronic technologies. According to the data protection method provided in embodiments of this application, after obtaining data related to a user in a plurality of manners, the electronic device may automatically determine a privacy degree of the data, for example, a privacy degree of identity information is high, and a privacy degree of itinerary information is low. The electronic device selects, based on different privacy degrees of the data, presentation manners corresponding to the different privacy degrees to present the data when the data needs to be presented, so that data with different privacy degrees can be differentially protected, and privacy security of the user can be ensured.