Privacy-Compliant Data Recording via Selective Obfuscation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems fail to consider individual consent for data recording in environments where multiple persons are present, limiting the use of observation data while compromising privacy.
Innovation Solution
A method and system that use sensors to identify and obfuscate private data of individuals who have not consented to recording, allowing for the generation of privacy-compliant data that can be stored and used for analysis, while respecting the privacy of non-consenting individuals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If all private data of persons in the environment is obfuscated to ensure privacy, then privacy protection is improved, but the usability and amount of available observation data deteriorates
Solution Approach 1:
The patent applies local quality by differentiating the treatment of data based on individual consent status. Instead of uniformly obfuscating all private data, the system selectively obfuscates only the private data of persons who have not consented to recording, while preserving the private data of persons who have given consent. This localized differentiation resolves the contradiction by protecting privacy where needed while maintaining data usability where permitted.
Solution Approach 2:
The patent segments the population of persons in the environment into distinct groups based on their consent status: those who have consented to recording and those who have not. This segmentation allows the system to apply different processing rules to different segments, thereby preserving valuable observation data from consenting individuals while still protecting the privacy of non-consenting individuals.
2Object-affected harmful factors
If strict privacy rules are applied to all persons in the environment, then privacy protection is improved, but the database size and data availability for analysis deteriorates
Solution Approach 1:
The patent implements local quality by applying different privacy protection intensities to different individuals based on their consent preferences. For persons who have consented to recording, no obfuscation is applied, maximizing data quality and quantity. For persons who have not consented, obfuscation is applied to protect their privacy. This localized approach ensures comprehensive privacy protection where needed while accumulating maximum possible data from consenting individuals, thereby increasing overall database size.
3Loss of information
If private data is selectively obfuscated based on consent status, then data usability is improved, but system complexity increases due to person identification and consent management
Solution Approach 1:
The patent applies preliminary action by obtaining consent from persons before recording their private data. The system proactively identifies persons, presents consent options, and records their preferences in advance. This preliminary consent management simplifies subsequent processing, as the system only needs to retrieve and apply the pre-recorded consent status rather than making complex real-time decisions about each person's privacy preferences.
Solution Approach 2:
The patent introduces an intermediary consent management mechanism that mediates between privacy protection requirements and data usability needs. This intermediary layer stores and manages consent information, allowing the system to automatically determine the appropriate level of obfuscation for each person based on their pre-recorded preferences, thereby simplifying the overall decision-making process.
Data Source
AI summary
The invention regards a method and system for recording observation data without violating privacy. Environment is sensed and observation data including information on the sensed environment is generated. The observation data is processed for determining presence of one or more persons in the sensed environment. Those person(s) amongst the present person(s) that did not agree to store their private data are identified and privacy compliant observation data is generated by obfuscating the private data of these persons. The privacy compliant observation data is store for later use.