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Finally, It’s discussion part.
Existing privacy-preserving approaches include differential privacy and GAN-based methods.
Differential privacy adds noise distorts the original data, resulting in a trade-off between model accuracy and privacy protection.
GAN-based approaches have high computational cost and long training time, which make them unsuitable for real-time data sharing systems.
In contrast, our proposal focuses on a data management mechanism without additional security modules.
However, our system has some limitations.
Specifically, it incurs additional preprocessing overhead compared to conventional methods.
In addition, locality may degrade when the shard size or geographical scope becomes large.
So, we plan to address these limitations in future work.
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IEEE/ICACT20260202 Slide.21
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