Use Pseudonymisation-Enabled Data Processing to:
Key Business Considerations
The telecommunications industry collects and uses personal data for a number of key reasons, including identifying customer network habits, managing infrastructure capacity, and carrying out security implementations. Using AI and Big Data analytics the telecommunications industry can monitor network and connection behaviour to look for security threats and to respond quickly. They also use personal data to:
However, the telecommunications industry is becoming increasingly aware of how this collection of personal data cannot be performed without appropriate technical measures and approaches, and in some cases GDPR enforcement actions have arisen.
For example, in late 2019, the federal German Federal Commissioner for Data Protection and Freedom of Information (BfDI) imposed a fine of €9.55 million (U.S. $10.6 million) on telecommunications provider “1 & 1” for GDPR violations. This was because they had not taken “sufficient technical and organizational measures” to prevent unauthorised people from obtaining information on customer data. This was in violation of the GDPR which requires that appropriate technical and organisational measures must be taken to protect personal data from both a security and privacy perspective.
Key Legal Considerations
For all of the reasons noted above, It is difficult to rely on the legal ground of consent for purposes of life sciences/healthcare research. This means that you need to rely on Legitimate Interests processing. Legitimate Interests processing provides benefits for data controllers wanting to lawfully use data for secondary processing and repurposing.
However, for Legitimate Interests processing to satisfy legal requirements, you must show that you are using “appropriate safeguards” that reduce the risk of data misuse, such as GDPR-compliant Pseudonymisation.
Anonos Pseudonymisation Technology
The problem is that until now, no data protection technologies were capable of supporting Legitimate Interests processing, by reconciling the conflict between data protection and utility when processing the personal data of customers to maximise lawful data value.
For example, conventional data protection technologies that support anonymisation, encryption, static token allocation, and differential privacy:
Click here to learn what other global companies have proven: that it is possible to retain up to 100% of the accuracy of analytical value when processing datasets protected using patented Anonos Variant Twins®.
Anonos state-of-the-art Pseudonymisation technology is superior to other data protection techniques because it helps enable lawful repurposing, distributed secondary processing and data sharing while delivering data utility equivalent to processing unprotected cleartext versions of personal data.