Implementing Signature Recognition System as SaaS on Microsoft Azure Cloud

The use of information technology in varied applications is growing exponentially which also makes the security of data a vital part of it. Authentication plays an imperative role in the field of information security. In this study, biometrics is used for authentication purpose and also describes the combinational power of biometrics and cloud computing technologies that exhibit the outstanding properties of flexibility, scalability, and reduced overhead costs, in order to reduce the cost of the biometric system requirements. The massive computational power and unlimited storage provided by cloud vendors make the system fast. The purpose of this research is to precisely design a biometric-based cloud architecture for online signature recognition on Windows Tablet PC, which will make the signature recognition system (SRS) more scalable, pluggable, and faster, thereby categorizing it under “Bring Your Own Device” category. For extracting the features of the signature to uniquely identify the user, Webber local descriptor (WLD) process is used. The real-time implementation of this feature extraction process as well as the execution of the classifier for the verification process is deployed on Microsoft Azure public cloud. For performance evaluation, total acceptance ratio (TAR) and total rejection ratio (TTR) are used. The proposed online signature system gives 78.10% PI (performance index) and 0.16 SPI (security performance index).