# Attribute-Centric and Synthetic Data Based Privacy Preserving Methods: A Systematic Review
## 4 Discussion on Synthetic Data-Based Privacy Methods
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Techniques Used** & **Objective (s)** & **Application Area** & **Study Type** & **Data Type** & **Reference** \\ \hline DP+ MERF approach & produce tabular and image data with privacy guarantees & General scenarios & Technical & Real & [PERSON] et al. [94] \\ DP-HFlow method & Privacy protection in data sharing & General Scenarios & Technical & Real & [PERSON] et al. [95] \\ Probabilistic modeling & Anonymized synthetic data sharing & Open science & Technical & Real and synthetic & [PERSON] et al. [96] \\ HealthGAN model & Better data analysis & Education and research & Technical & Synthetic & [PERSON] et al. [97] \\ GAN+ XAI & High quality SD generation & Health data & Technical & Real & [PERSON] et al. [98] \\ HealthGAN model & Capturing trends from TSD & Medical domain & Technical & Real and synthetic & [PERSON] et al. [99] \\ VGAE model & Yield artificial trajectories with PPP & Electronic health & Technical & Synthetic & [PERSON] et al. [100] \\ VITALISE model & Compliance-based data use & Health and well-being domain & Technical & Real & [PERSON] et al. [101] \\ GAN model & Reduce risk of SA disclosure & Fitness related & Technical & Real & [PERSON] et al. [102] \\ SDG framework & Privacy preservation & Medical domain & Technical & Real & [PERSON] et al. [103] \\ dsSynthetic package & Data harmonization & General scenarios & Technical & Real & [PERSON] et al. [104] \\ STSG approach & Privacy guarantees & General scenarios & Theoretical & Real & [PERSON] et al. [105] \\ pGAN model & Privacy guarantees & Medical domain & Technical & Real & [PERSON] et al. [106] \\  & in EHR & & Medical domain & Technical & Real and synthetic & [PERSON] et al. [107] \\ VAE model & Fixation of bias and privacy & Medical systems & Technical & Real & [PERSON] et al. [108] \\ Neural-Prophet & Maintaining validity & Medical systems & Technical & Real & [PERSON] et al. [108] \\ model & Measure of MD & Accurate clinical & & & \\ Transformer models & predictions with privacy guarantees & healthcare & Technical & Real & [PERSON] et al. [109] \\ HealthGAN model & Privacy, utility, and resemblance & Healthcare domain & Technical & Real & [PERSON] et al. [110] \\ GANs models & Data augmentation & General scenarios & Technical & Real & [PERSON] et al. [111] \\ GAN model & Control on various privacy risks & Big data apps & Theoretical & Real & [PERSON] et al. [112] \\ MC-GEN model & Privacy guarantees & ML applications & Technical & Real & [PERSON] et al. [113] \\ PPEA model & Better utility of data & Distributed environments & Technical & Real & [PERSON] et al. [114] \\ DP+ GAN & Higher privacy guarantees & Industrial IoT & Technical & Real & [PERSON] et al. [115] \\ \((\epsilon,\delta)\) -ULDP & Strong privacy protection & General scenarios & Technical & Real, synthetic & [PERSON] et al. [116] \\ _Fed Select_ Framework & Strong privacy guarantees in FL & IoMT settings & Technical & Real & [PERSON] et al. [117] \\ LGAN + DP & Privacy-utility & ML applications & Technical & Real & [PERSON] et al. [118] \\ HT-Fed-GAN model & Privacy-utility & machine learning & Technical & Real & [PERSON] et al. [119] \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Summary and comparisons of the most recent synthetic data-based privacy methods. Recently, synthetic data (SD) have become an indispensable component for AI applications, and therefore, many generative models were recently developed to compensate for the deficiency in good data [120, 121]. The SD generated with the generative models has lots of applications in diverse fields such as medical image analysis, fault diagnosis, language models, image recognition, and medical diagnosis, to name a few. Furthermore, some companies are sharing SD rather than real data to overcome privacy concerns. Figure 8 presents SD-based developments along with the experimental details. We classify the SD generation process into four key steps, as marked in by the color yellow.