Most companies and research institutes restore to data de-identification with the help of specially designed software in order to protect their privacy of the data source. This software gives the user the possibility of an accurate measurement for the risks of re-identification as it deidentifies data to keep individual privacy intact while retaining the value of data. The list of benefits for using deindetification is quite long, and the optimization of data is amongst the most important as it offer cross-sectional, longitudinal and geospatial optimization. Ensuring high utility of information and making it acceptable by a high number of analysts is another benefit along side the scientifically-validated and leverages peer-reviewed methodology that is based on risk that indicates the exact amount of de-identification that needs to be applied to the data.
Moreover, re-identification risks in certain circumstances are accurately measured, while the used tools that are meant to simulate the attacks will lead to performing sensitive analysis and enabling users to test different scenarios. It can also de-identify your data sets no matter if we're talking about massive or local databases. Additionally, the de-identification software can generate certificates, which document data sets have small chances to re-identify, and saves the specifications of the program to let it run on other databases. Besides all these benefits that you can acquire by using the software, you should understand its actual working mechanism in order to understand the entire process, and there are four easy steps that need to be followed in order to use it on your own. First, you need to choose the indirect identifiers and the chosen variables need to be ranked so that they can be used for the re-identification of the data. During the de-identification process, the ranking is needed to decide which would be the optimal anonymization in order to keep in balance the re-identification risk and data utility.
The next step is to set de risk limit of re-identification as the software allows the user to adjust the threshold in accordance with what is acceptable to him based on the profile of the individual or corporation requesting confidentiality. This is an essential step for keeping the balance between data granularity and privacy since this risk-based process guarantees that data utility is kept while individual privacy is safeguarded. The third step consists in carrying out the risk analysis by calculating the data set's risk for journalist, prosecutor and assault-marketer, which represent the three types of re-identification. Finally, you need to de-identify in order to protect your information, and here you can use several techniques. For instance, suppression or elimination of the high risk values in your database and generalization or reducing the resolution of a certain field are only two of the available techniques.
To summarize, the de-identification software will de-identify the data automatically so that the risk of re-identification will be set to a minimum level according to the legislation and the user. Moreover, with the help of this software you can even create data sharing agreements for the de-identified data set.
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