Participatory Sensing Privacy Protection With Encrypted Participant Chains
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Solution Overview
Problem
In participatory sensing, the privacy of participants is at risk due to exposure of their trajectories and data, which can be used to infer personal information, and this disclosure aims to protect participant privacy while maintaining data quality and incentive alignment.
Innovation Solution
The system employs a participant selection process based on inferable privacy levels, data encryption with unique random identifiers, and a participant chain structure to ensure that sensory data is not linked to participant identities, combined with a security multiparty scalar product protocol to determine incentives and organize participant chains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If centralized participant selection is used to optimize data collection quality, then data quality is improved, but participant privacy is exposed through trajectory information
Solution Approach 1:
The patent introduces a privacy protection mechanism as an intermediary layer between the application server and participant data. The server receives encrypted sensory data and incentive information without being able to trace them back to specific participants, thus mediating between data collection needs and privacy protection requirements
Solution Approach 2:
The patent extracts and removes the identifying information (trajectories and participant identities) from the data transmission process. Participants upload sensory data without their trajectory information being exposed to the application server, effectively taking out the harmful element while preserving data utility
2Measurement precision
If the application server tracks data sources and incentive destinations, then incentive distribution accuracy is improved, but participant privacy is compromised
Solution Approach 1:
The patent uses encryption and anonymous identifiers as intermediaries to enable accurate incentive distribution without direct tracking. The server can distribute incentives precisely to the correct participants through cryptographic mechanisms without knowing their real identities or trajectories
Solution Approach 2:
The patent creates anonymous copies of participant identifiers through encryption. The server works with encrypted identifiers that function as substitutes for real identities, allowing accurate tracking and distribution while protecting the original identity information
3Quantity of substance
If participants contribute significant proportions of sensory data, then data coverage is improved, but their privacy is exposed through identification
Solution Approach 1:
The patent introduces encrypted identifiers as intermediaries that allow the server to recognize and reward significant contributors without exposing their identities. The mediation mechanism preserves the ability to identify major data contributors for incentive purposes while protecting their privacy through encryption
Solution Approach 2:
The patent applies different levels of anonymity to different aspects of data handling. While trajectory information is completely anonymized, the system maintains local quality by preserving the ability to identify contributors at the incentive distribution level through cryptographic means
4Device complexity
If traditional data collection methods are used, then implementation simplicity is maintained, but privacy protection is insufficient
Solution Approach 1:
The patent introduces encryption and anonymous identifiers as intermediary mechanisms that can be integrated into existing data collection workflows. These intermediaries add privacy protection without fundamentally changing the overall system architecture or data collection process
Data Source
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AI summary
Method, apparatus, computer program product and computer readable medium are disclosed for privacy protection. A method may comprise: receiving encrypted data from a top participating node of a participant chain, which comprises a plurality of participating nodes; and decrypting the encrypted data, wherein the encrypted data comprise a plurality of encrypted sensory data obtained respectively by said plurality of participating nodes.