Usage-Controlled Image Generation for Privacy Compliance
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Solution Overview
Problem
Current mechanisms for controlling personal data usage fail to effectively prevent unintended uses while maintaining recognizable formats, leading to potential misuse and violating data privacy regulations.
Innovation Solution
A system comprising a processor, face recognizer, face matcher, and image usage controller transforms input images into usage-controlled formats that prevent identity recognition for unintended purposes while preserving face matching characteristics, ensuring compliance with data usage policies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complex cryptographic computations are applied to personal data, then data privacy is improved, but the personal data becomes completely non-recognizable and loses its original characteristics
Solution Approach 1:
The patent segments the personal data processing into two distinct functional paths: one path applies cryptographic transformations to protect privacy-sensitive attributes, while another path preserves original characteristics for legitimate uses. This segmentation allows different portions of the data to be treated differently based on their usage requirements, resolving the contradiction between privacy protection and data recognizability.
Solution Approach 2:
The patent applies local quality by implementing usage-specific data transformations where only the portions of personal data required for specific purposes are protected or transformed. Different data elements receive different levels of protection based on their intended use, allowing the system to maintain original characteristics where needed while applying privacy protections where required, rather than uniformly transforming all data.
2Object-affected harmful factors
If personal data is transformed into a non-recognizable format, then unintended usage is prevented, but the data cannot be used for its intended purpose either
Solution Approach 1:
The patent implements dynamic data transformation where the level and type of transformation applied to personal data changes based on the intended purpose. The system adaptively selects transformation strategies that prevent unintended uses while preserving necessary characteristics for legitimate purposes, making the data protection mechanism flexible rather than static.
Solution Approach 2:
The patent changes parameters of data transformation based on usage context. By adjusting transformation intensity and type according to the specific purpose, the system prevents unintended usage (by applying sufficient transformation) while maintaining data usability (by preserving necessary characteristics), resolving the contradiction between protection and adaptability.
3Reliability
If stricter compliance mechanisms are implemented, then data privacy regulation adherence is improved, but the complexity of the system increases
Solution Approach 1:
The patent applies preliminary action by implementing data transformation and usage control mechanisms before data is actually used. By pre-establishing usage policies, transformation rules, and access controls, the system ensures compliance is built into the data processing workflow from the start, reducing the need for complex monitoring and enforcement mechanisms later.
Solution Approach 2:
The patent introduces intermediary components that mediate between raw personal data and usage processes. These intermediaries handle transformation, validation, and control functions, simplifying the overall system architecture by centralizing compliance logic in dedicated components rather than distributing complexity throughout the entire system.
Data Source
AI summary
Examples of a system for usage control of a personal data are described. The system may obtain an input image including a first face of a person. Further, the system may compute a usage control matrix based on the input image, at least one usage control function, and a predefined criteria. The pre-defined criteria may be associated with at least one of: a data usage policy, a face matching probability related to matching of the face present in the input image, and a face recognition probability related to a recognition of an identity of the person. Furthermore, by using the input image and the usage control matrix, the system may transform the input image to a usage-controlled image. Furthermore, the system may verify a matching of the face present in the input image with a second face present in the usage-controlled image. Furthermore, the system may recognize an identity of the person in the input image and provide a feedback indicative of a failure to verify the identity of the person from the usage-controlled image.