The Creation of Custom Data Sets to Meet Customer Needs: A BSC Project
Rapidly advancing technology and the growing need for accurate and efficient data analysis have led organizations to seek customized data sets tailored to their specific needs.
Data masking is essential to ensure the privacy of sensitive data. By eliminating sensitive information or replacing it with fictitious or altered data, its exposure is reduced and the privacy of the individuals or entities involved is protected. This is especially relevant when handling personal, financial or health-related data, as it helps prevent unauthorized disclosure and reduces the risk of identity theft, fraud or other privacy breaches.
In addition to protecting privacy, data masking is necessary for complying with data privacy regulations and standards. For example, the European Union's GDPR establishes strict requirements for the protection of European citizens' personal data, and data masking is an effective measure to comply with these legal obligations. Similarly, the HIPAA in the United States mandates health data protection, and data masking can help comply with these regulations.
Another important reason for using data masking is to mitigate the risk of insider threats. Many data breaches occur due to employees or privileged users accessing sensitive information in an unauthorized manner. By masking the data, the exposure of real information is limited and the possibility of misuse or unauthorized disclosure of data by insiders is reduced.
One more area where data masking is necessary is in software development and testing. Masking allows developers to work with realistic data without exposing real sensitive data, ensuring data security and privacy. In addition, data masking facilitates collaboration and data sharing for development and testing purposes without compromising the confidentiality of the information.
Related content: Why All Companies Should Use Data Anonymization
When it comes to data masking, there are multiple techniques with which you can maintain data privacy. Among all the existing techniques, we will highlight the following:
Data masking is an increasingly important technique for protecting the privacy and confidentiality of sensitive data. To protect your data with data masking, you must first identify the sensitive data that needs to be protected. Next, it is important to classify the data according to its level of sensitivity and decide which masking techniques should be applied to each type of data.
Masking techniques can include any of the techniques explained above. It is important to apply the appropriate anonymization techniques to each type of data to ensure that it is being adequately protected and that it cannot identify individuals or reveal confidential information.
Once masking techniques have been applied, it is important to evaluate the masked data to ensure that it has been adequately protected. It is always necessary to implement a security policy for handling sensitive data and data masking. It is also important to perform security tests to detect possible vulnerabilities or weaknesses in data masking and take preventive measures.
By following the above steps, you can protect your data and ensure that it is handled properly and securely. By doing so, you can ensure that sensitive data is protected and not exposed to potential security threats.
Recommended reading: Best data anonymization tools and techniques
When selecting a possible data masking solution for data privacy, several factors must be taken into account. Some of them are as follows:
Taking these aspects into account can help to choose an effective and efficient solution to protect an organization's sensitive data.
Data masking is one of the most important measures that can be taken to protect privacy and information security. This involves not only implementing effective data masking techniques, but also ensuring that they are used appropriately and responsibly at all stages of the data's life cycle. By taking steps to effectively protect data, we can ensure the confidentiality, integrity and availability of information, which is critical for security and privacy in today's digital world.
At Pangeanic, we offer a complete and customized anonymization solution using various techniques for the removal of identifiers from a database, documents or publications. With our technology, traces and clues that could expose confidential details are destroyed. We give our clients the possibility to choose the technique they prefer when masking the data.
The solution we have developed is called Masker, a data masking system that automatically detects personally identifiable information and allows you to adjust the level of sensitivity of the process through different techniques.
As mentioned above, this is a customized solution, so apart from the basic masking that our system performs, we give our clients the option to customize the system to their liking. In this way, you can select the types of data you want to mask (people, organizations, etc.) and the type of masking, as well as create or request the regular expressions to mask new data patterns not covered by our system, among other options.
This solution is available on our AI-based language processing platform called ECO, which, apart from offering data masking or anonymization solutions, also has solutions for both pseudonymization and machine translation.
Rapidly advancing technology and the growing need for accurate and efficient data analysis have led organizations to seek customized data sets tailored to their specific needs.
The technological advances that have occurred over the course of the last few decades have made it possible to optimize and streamline the work of human translators. One of these advances is machine translation (MT).
Synthetic data is data that has been artificially generated from a model trained to reproduce the characteristics and structure of the original data. The goal is for the synthetic data to be sufficiently similar to the...