## 3 ShinyAnonymizer: Key Features and Functionality
### Technical Details of Anonymization Techniques  
* Description: Generalization means substituting particular data values with higher but exact categories. For instance, age ranges can be utilized instead of real ages. This method reduces the resolution of the data, rendering it harder to determine individuals while maintaining important aggregate data. * Application: Generalization efficiently handles sensitive variables like age, wealth, or geographic location. It is a usual approach for scenarios when unique individual data is not necessary, but patterns or trends must be analyzed. * _Removing Information_
* Description: This method requires eliminating specific identifiable data from the dataset. For instance, it removes names, social security numbers, and other direct identifiers from a database. * Application: Removal is easy, but it might not always be sufficient, mainly since indirect identifiers can still be utilized to re-identify an individual. It is often employed together with other anonymization techniques to enhance privacy. * Description: Suppression involves concealing or hiding particular data values. For instance, sensitive variables can be replaced with a common placeholder (e.g., substituting a patient's true gender with an asterisk \"*\") or parts of data (e.g., only disclosing the initial three digits of a social security number). * Application: Suppression is often used to protect highly sensitive data that cannot be generalized without drastically decreasing the data utility. It is beneficial when just a tiny amount must be preserved while permitting a specific data analysis. * _Bottom Coding_
* Description: Bottom coding allows data to be divided into more significant categories, particularly with variables with an extensive range of values. Earnings levels, for example, may be categorized as \"low,\" \"medium,\" or \"high\" instead of offering actual statistics. * Application: Bottom coding minimizes the risk of re-identification by grouping individual data points into larger groups, rendering it less likely that every individual data will be wiped out. It is often employed with different methods to guarantee data privacy while permitting helpful research. All the techniques were chosen, to find the right balance between privacy and data utility. Once methods of anonymization are used, an extensive evaluation process is required. Evaluation means deciding if personal characteristics have been successfully removed by the methods of anonymization and if the data still have enough quality to be utilized for what was intended. The process makes sure that each person's privacy is well safeguarded, despite the anonymized data's analytical value. After confirmation, the anonymized dataset may be transmitted or maintained without risks. This planned strategy optimizes the privacy and security of data by permitting businesses to effectively utilize their data, while following legal and ethical guidelines [15]. Also, compared to perturbation, which demands adding noise to data, generalization swaps bigger groups for specific items [16]. All the methods were chosen to find the right balance between privacy and data utility. Once methods of anonymization are used, an extensive evaluation process is required. Evaluation means deciding if the methods of anonymization have successfully removed personal characteristics and if the data still has enough quality to be utilized for what was intended. The process ensures that each person's privacy is well safeguarded despite the anonymized data's analytical value. After confirmation, the anonymized dataset may be transmitted or maintained without risks. This planned strategy optimizes the privacy and security of data by permitting businesses to effectively utilize their data, while following legal and ethical guidelines [17]. A brief description of our anonymization process is provided in Figure 1: Beginning with the database identification, the data anonymization process takes place immediately.