A Different Level Text Protection Mechanism With Differential Privacy
arXiv:2409.03707v11 citationsh-index: 3
Originality Synthesis-oriented
AI Analysis
This work addresses privacy protection in text data, but it appears incremental as it builds on existing BERT-based approaches without introducing a major breakthrough.
The paper tackles text protection by extracting words of varying importance using BERT and analyzing how consistent perturbation affects text utility, demonstrating the method's effectiveness for long texts.
The article introduces a method for extracting words of different degrees of importance based on the BERT pre-training model and proves the effectiveness of this method. The article also discusses the impact of maintaining the same perturbation results for words of different importance on the overall text utility. This method can be applied to long text protection.