Clipboard Sync Prediction and Privacy Screening
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Solution Overview
Problem
Existing clipboard syncing techniques in remote computing environments are inefficient, as they transfer data unnecessarily, cause delays in large data transfers, and consume network resources, while users are concerned about data privacy and security.
Innovation Solution
Implementing a system that evaluates historical data to predict copy and paste operations and only transfers data when likely to be used, and uses privacy screening techniques to determine if data contains private information before transfer, allowing users to override privacy concerns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is transferred from local buffer to remote computing environment, then data synchronization is achieved, but network resources are consumed and transfer delays occur
Solution Approach 1:
The system performs preliminary actions by evaluating historical data to predict whether copied data will be pasted in the remote environment before actually transferring the data. This allows the system to prepare and prioritize transfers intelligently, reducing delays by pre-processing and pre-transferring predicted data while maintaining synchronization reliability.
2Reliability
If data is transferred from local buffer to remote computing environment, then data synchronization is achieved, but network resources are consumed
Solution Approach 1:
The system applies partial action by transferring only the subset of copied data that is predicted to be pasted in the remote environment, rather than transferring all copied data. This selective transfer approach maintains necessary synchronization while conserving network resources by avoiding unnecessary data transmissions.
3Reliability
If all copied data is transferred to remote environment, then complete synchronization is achieved, but private information may be exposed
Solution Approach 1:
The system extracts and identifies private information from copied data using evaluation techniques before transfer. By separating and detecting sensitive content, the system can exclude private information from transfer while maintaining synchronization of non-sensitive data, thus preventing privacy exposure while achieving necessary synchronization.
4Object-affected harmful factors
If data transfer is restricted for privacy reasons, then data security is improved, but synchronization efficiency decreases
Solution Approach 1:
The system implements feedback by continuously evaluating historical data transfer patterns and user behavior to improve predictions of which copied data will be pasted remotely. This feedback loop allows the system to refine its selective transfer decisions, maintaining high synchronization efficiency for predicted data while enforcing privacy protections, thus resolving the efficiency-privacy tradeoff.
Data Source
AI summary
A computing system may determine that first data was copied from a first application to a buffer of a first computing environment, and that the first data was received by a second application in a second computing environment. The computing system may identify second data copied from the first application to the buffer and, in response to the second data being copied from the first application to the buffer and based at least in part on the second application having received the first data, may cause the second data to be transferred from the buffer to the second computing environment. The computing system may further evaluate the second data to determine whether it includes potentially private information, and may cause the second data to be transferred to the second computing environment based at least in part on the second data being free of potentially private information.