A new metric developed by the Carlos III University of Madrid and the National Cybersecurity Institute allows for a more precise measurement of user privacy in digital databases. The advancement has been presented after applying the method to platforms such as LinkedIn, X, and Meta.
A Probabilistic Approach to Digital Privacy
The research team has published the results in the scientific journal Array. Rubén Cuevas Rumín, deputy director of the UC3M–Banco Santander Joint Research Institute in Financial Big Data, explains that traditional K-anonymity is insufficient to guarantee real user protection. According to Cuevas, this method only indicates how many people are exactly the same as a user within a database, without reflecting the actual level of protection.
"K-anonymity has been used for years, but it only measures how many people are exactly like you within a database, so it doesn't reflect whether a user is truly well-protected or not" - Rubén Cuevas Rumín, UC3M
The new metric incorporates probabilistic information and estimates the likelihood that an individual resembles another user, taking into account variables such as age, gender, and interests. This approach allows for a more detailed analysis of the level of anonymity offered by different digital platforms.
Results on Platforms and Recommendations
Researchers have found that LinkedIn and X offer greater privacy protection than Meta. Furthermore, small changes in how data is stored can have a significant impact on privacy. For example, replacing a user's exact age with an age range could improve Meta's privacy level more than tenfold.
"With very simple changes, like replacing a user's exact age with an age range, Meta could improve its privacy level more than tenfold" - Rubén Cuevas Rumín, UC3M
The study underscores the importance of society knowing which databases store their information and what level of protection they offer. Data leaks can lead to dangerous practices if systems are not well designed.
"It is essential that society pays attention to which databases are storing their information and what protection they offer, as leaks can lead to dangerous practices if systems are not well designed" - Rubén Cuevas Rumín, UC3M
ANTICIPA Project and European Funding
The development of this metric is part of the ANTICIPA project, an agreement between INCIBE and UC3M. The initiative is included in the Strategic Projects in Spain and has funding from the Next Generation-EU Funds, within the framework of the Recovery, Transformation and Resilience Plan.
- The metric has been applied on LinkedIn, X, and Meta
- The method uses data such as age, gender, and interests to estimate privacy
- The project has the support of European funds