Publication

Abstract : Big data is an emerging technology that is becoming an essential part of national governance. Aadhaar is the unique identification scheme of India, handled by the Unique Identification Authority of India (UIDAI), which deals with big data. Every person above the age of 5 years has to register their demographic details (Name, Date of Birth, Address and Phone number) and biometric details (10 fingerprints and both iris) and then these details are used to verify the authenticity of the person when any services are required by him. Passport is a legal document that is carried by a person when he travels between countries, but in the case of the older passports with no biometric data, a person may have more than one legal passport with different demographic details. This paper does a case study on the existing de-duplication methods for passport enrolments and other such documents. In the case of newer passports, it takes 10 days to link with Aadhaar at the time of registration, hence the aim is to reduce the processing time of the linking and verification. String matching algorithms are used to compare the demographics, and techniques such as genetic programming and hashing are used for de-duplication. This case study also helps identify big and fast data platforms to identify such e-governance plans, by evaluating the accuracy and efficiency of existing algorithms. This system aims to predict the duplication of passports by linking Aadhaar and passport details, and to reduce the processing time of the Aadhaar database by using parallel algorithms.