Part 4/11:
Participants also highlighted societal practices, such as the unsafe safekeeping of law enforcement's small arms—often dismantled into parts and stored separately—as an analogy to data security. The consensus was that dispersing or disaggregating data reduces risk, a principle that could be applied through PETs.
Privacy-Enhancing Technologies: The Future of Data Trust
The core message was clear: post-DPDP, PETs are poised to become fundamental in managing data privacy. These technologies—including anonymization, differential privacy, federated learning, and secure multi-party computation—enable organizations to analyze and derive value from data without compromising individual identities.