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abstract

Veri-Pen: A Pen-based Identification Through Natural Biometrics Extraction

Published:07 May 2016Publication History

ABSTRACT

As we live in the Internet age, we face high threats of data leakage, identity theft, and inconvenience over authenticating ourselves online. Safe and simple digital identification is crucial in the digital realm. In order to solve the above issues, a mediating digital assistive device could possibly act between the user and computer system in order to replace the current identification system. In this paper I present Veri-Pen, a stylus that provides digital identification through the natural extraction of a signature and fingerprint. The proposed concept aims to deliver simple and secure pen-based online identification. The prototype, built upon user case studies, was evaluated in a simulated scenario of digital authentication in comparison to conventional ID-password identification. The user evaluation confirmed that the pen-based identification tool with biometrics delivers a simple and trustworthy experience to users during the procedure of authentication.

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  1. Veri-Pen: A Pen-based Identification Through Natural Biometrics Extraction

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    • Published in

      cover image ACM Conferences
      CHI EA '16: Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems
      May 2016
      3954 pages
      ISBN:9781450340823
      DOI:10.1145/2851581

      Copyright © 2016 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 7 May 2016

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      Acceptance Rates

      CHI EA '16 Paper Acceptance Rate1,000of5,000submissions,20%Overall Acceptance Rate6,164of23,696submissions,26%

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