The largest biometric deployment in history is now underway in India, where the Government is
enrolling the iris patterns (among other data) of all 1.2 billion citizens. The purpose of the Unique
Identification Authority of India (UIDAI) is to ensure fair access to welfare benefits and entitlements,
to reduce fraud, and enhance social inclusion. Only a minority of Indian citizens have bank accounts;
only 4 percent possess passports; and less than half of all aid money reaches its intended recipients.
A person who lacks any means of establishing their identity is excluded from entitlements and does
not officially exist; thus the slogan of UIDAI is: To give the poor an identity." This ambitious
program enrolls a million people every day, across 36,000 stations run by 83 agencies, with a 3-year
completion target for the entire national population. The halfway point was recently passed with
more than 600 million persons now enrolled. In order to detect and prevent duplicate identities, every
iris pattern that is enrolled is first compared against all others enrolled so far; thus the daily workflow
now requires 600 trillion (or 600 million-million) iris cross-comparisons. Avoiding identity collisions
(False Matches) requires high biometric entropy, and achieving the tremendous match speed requires
phase bit coding. Both of these requirements are being delivered operationally by wavelet methods
developed by the author for encoding and comparing iris patterns, which will be the focus of this
Large Data Award" presentation.