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Implementing Signature Recognition System as SaaS on Microsoft Azure Cloud

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Data Management, Analytics and Innovation

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 808))

Abstract

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).

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Acknowledgments

It is my great pleasure to express my sincere gratitude to my colleague, Ms. Dhvani Shah, for her unwavering support to carry out this entire research. I am also immensely grateful to Microsoft Azure for awarding me a research grant of $5000 to carry out this research on their cloud infrastructure.

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Authors and Affiliations

  1. Universal College of Engineering, Mumbai, Maharashtra, India

    Joel Philip

  2. St. John College of Engineering and Management, Palghar, Maharashtra, India

    Dhvani Shah

Authors
  1. Joel Philip
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  2. Dhvani Shah
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Corresponding author

Correspondence to Joel Philip .

Editor information

Editors and Affiliations

  1. Department of Automatics and Applied Software, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

  2. Audyogik Tantra Shikshan Sanstha’s, IICMR, Pune, Maharashtra, India

    Neha Sharma

  3. Faculty of Engineering and Technology, A. K. Choudhury School of Information Technology, Kolkata, West Bengal, India

    Amlan Chakrabarti

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Philip, J., Shah, D. (2019). Implementing Signature Recognition System as SaaS on Microsoft Azure Cloud. In: Balas, V., Sharma, N., Chakrabarti, A. (eds) Data Management, Analytics and Innovation. Advances in Intelligent Systems and Computing, vol 808. Springer, Singapore. https://doi.org/10.1007/978-981-13-1402-5_36

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  • DOI: https://doi.org/10.1007/978-981-13-1402-5_36

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1401-8

  • Online ISBN: 978-981-13-1402-5

  • eBook Packages: EngineeringEngineering (R0)

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