Identification and authentication play a significant role in security controls. The manual process of user identification and authentication is time-consuming and tedious. The proposed research work aims to overcome this drawback and achieve user identification and authentication through an automated method using the Aadhar card. Aadhar project is developed by the Unique Identification Authority of India by merging biometrics and digitization. The details are stored in the form of a quick response code along with a 12-digit Aadhar card number. A model is built to capture the information from the Aadhar card. The mobile phones are used to obtain the data from the Aadhar card. The user validation is through two-step process using One Time Password and email address. The wireless public key infrastructure issues a digital certificate to the valid user. The proposed authentication and symmetric key exchange algorithm are formally verified and analyzed using automated validation of Internet security protocols and applications. The result of simulation proves that the proposed scheme is secure and safe. The experimental results show that time consumption for user authentication is acceptable. The acceptance of the proposed automated user identification and authentication model is authorized using a modified technology acceptance model. The result proves that there exists a strong relationship between the perceived usefulness of items and the Attribute Of Use (AOU). It also exhibits that the association between the AOU and user satisfaction is influential. The model demonstrates that the association between the Perceived Ease Of Use and attribute towards use is weak. The influence of exogenous variables over endogenous variables exhibits that the proposed model outperforms the traditional manual system and the target users are inclined towards it. The proposed model also finds its application in services which requires user authentication.
|Number of pages||27|
|Publication status||Published - 01-01-2019|
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Materials Science(all)