Privacy-Enhanced Sensor Data Disclosure via Derived Predicates
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Solution Overview
Problem
Traditional sensor-based systems lack intelligent analysis capabilities without vast amounts of tagged data, and there is a need for techniques that can provide deeper understanding of observed spaces and react optimally while ensuring user privacy, especially in the context of IoT device deployments.
Innovation Solution
The system determines a representation of sensor data, computes privacy impact indicators, and controls access to this data based on user permission feedback, using predicates generated from sensor data to provide a privacy-enhanced interface for users and third-party service providers, allowing selective data sharing while maintaining user privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traditional sensor-based systems are used without vast amounts of tagged data, then device complexity and data storage requirements are reduced, but analysis capability and understanding of observed spaces deteriorate
Solution Approach 1:
The patent extracts and shares only specific derived information (predicates) from sensor data rather than sharing all raw sensor data. This extraction approach enables third-party service providers to perform analysis while the user retains control over their raw data, resolving the contradiction between reducing data storage requirements and maintaining analysis capability.
Solution Approach 2:
The patent transforms raw sensor data into different parameter representations (predicates) that convey meaningful information about observed spaces. By changing the parameter form from raw data to derived predicates, the system maintains analytical value while reducing the volume of data that needs to be stored and managed.
2Adaptability or versatility
If raw sensor data is shared with third-party service providers, then service functionality and adaptability are improved, but user privacy and security deteriorate
Solution Approach 1:
The patent introduces predicates as an intermediary layer between raw sensor data and third-party service providers. These predicates serve as a mediator that conveys necessary information for service functionality while protecting user privacy by not exposing the underlying raw data. This resolves the contradiction by enabling service adaptability through the intermediary predicate layer.
Solution Approach 2:
The patent segments information into different levels: raw sensor data held privately by users, and derived predicates shared with third parties. This segmentation allows service providers to access processed information for functionality while users maintain control over their sensitive raw data, thus protecting privacy while enabling service versatility.
3Adaptability or versatility
If derived data predicates are shared with third-party service providers, then service provision capability is improved, but information security requirements increase
Solution Approach 1:
The patent extracts only the necessary derived information (predicates) needed for service provision while leaving the sensitive raw data secured with the user. This extraction approach improves service capability by providing third parties with useful processed data while maintaining information security by not exposing the full data set.
4Object-affected harmful factors
If user permission feedback is implemented for data access control, then user privacy control is improved, but system operation complexity increases
Solution Approach 1:
The patent implements preliminary action by obtaining user permission feedback before sharing derived data predicates with third-party service providers. This preliminary permission step establishes privacy control upfront, allowing the system to operate smoothly thereafter without requiring continuous user intervention, thus balancing privacy control with operational simplicity.
Data Source
AI summary
An apparatus in an illustrative embodiment comprises at least one processing device comprising a processor coupled to a memory. The processing device is configured to determine a representation characterizing data from one or more sensor devices of at least one sensor network, to determine a privacy impact indicator for the data, to provide the representation and its associated privacy impact indicator for presentation in a user interface of a user device, and to control access to information relating to at least portions of the data by one or more third party service providers based at least in part on user permission feedback relating to the representation and its associated privacy impact indicator as presented in the user interface of the user device. Other illustrative embodiments include methods and computer program products.