Nowadays new laws and regulations to prevent the privacy of users have been proposed. For instance, the General Data Protection Regulation (GDPR) is taking effect in Europe, requiring organizations to define privacy policies complying with the preferences of their users. One way to abide by GDPR is to obscure sensitive data. However, in order not to limit the usage of data, it is vital to limit the amount of data to be obscured. To this end, we propose a methodology exploiting relaxed functional dependencies (rfds) to automatically identify attributes from which sensitive values can be derived. The methodology prescribes to partially encrypt database values causing data privacy threats, identified through the automatically discovered rfds.
A methodology for GDPR compliant data processing
Desiato D.
;Tortora G.
2018-01-01
Abstract
Nowadays new laws and regulations to prevent the privacy of users have been proposed. For instance, the General Data Protection Regulation (GDPR) is taking effect in Europe, requiring organizations to define privacy policies complying with the preferences of their users. One way to abide by GDPR is to obscure sensitive data. However, in order not to limit the usage of data, it is vital to limit the amount of data to be obscured. To this end, we propose a methodology exploiting relaxed functional dependencies (rfds) to automatically identify attributes from which sensitive values can be derived. The methodology prescribes to partially encrypt database values causing data privacy threats, identified through the automatically discovered rfds.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
