Hybrid Model Based on User Tags and Textual Passwords and Pearsonian Type III Mixture Model
Journal: International Journal of Advanced Engineering Research and Science (Vol.4, No. 3)Publication Date: 2017-03-08
Authors : Pavan Gujjar Panduranga Rao; Dr.P.Srinivasa Rao; G. Lavanya Devi;
Page : 245-251
Keywords : Graphical Password Authentication; Pearsonian Type III Mixture Model; Statistics; Probabilistic model; MIR Flickr.;
Abstract
The latest advancements in Science and Technology, have witnessed radical changes in the banking system. Today most of the banks adopt the net banking facility and most of the users are also addicted to this system. Accordingly, most of the transactions are now online based and much emphasis is therefore needed to ensure the security of authenticating a person and validating the transaction. Many models are therefore proposed in the literature. Most of these are an alphanumeric based password schemes or biometric schemes or graphical password based schemes. Each of these models is proposed by underlying an advantage. The alphanumeric passwords are proposed, with the assumption that generating the password is easy and the generated password is unique, the biometric password schemes are proposed with the assumption that tampering a biometric is next to impossible. Graphical passwords are proposed with an option to the user so that he can select an image of his choice and then select some points which is called a click pattern, which is unique to every user.
Other Latest Articles
- A Slotted-sense Streaming MAC for Real-time Multimedia Data Transmission in Industrial Wireless Sensor Networks
- High Frequency Gas Tungsten Arc Welding Process for Dressing of Weldment
- SOCIOLOGICAL ANALYSIS OF THE ACHIEVEMENTS AND CHALLENGES OF SOCIAL MEDIATION IN SOCIAL WORK WITH FAMILIES HAVING CHILDREN-INVALIDS
- A Novel Study of Semiconductor Material as a Substrate Layer for Microstrip Patch Antenna
- Strain Measurement Using Fiber Bragg Granting Sensor for Crack Detection
Last modified: 2017-04-02 18:54:49