eSignature Verification on Web Using Statistical Mining Approach

  • Joseph Fong
  • San Kuen Cheung
  • Irene Kwan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2642)


This research is related to the field of biometrics. The biometrics research consists of fingerprint scans, retina scans, voiceprint analyses, and so on [1]. Although an electronic signature (eSignature) does not actually come from human, it comes from an indirect tissue (i.e. handwriting) of a human. For instance, a handwritten signature will be collected from a cardholder when filling out the application form of credit card and formularized from a normal signature to an electronic signature. This eSignature will then be transmitted and stored into XML document in a data center. We will extract the eSignature that is a group of numbers from the database. This group of numbers is a factor in preceding the Online Analytical Mining (OLAM) [2]. We use the Internet as a network channel. We will also use the XML-RPC [6] to implement the active rules and apply OLAM to verify incoming eSignatures.


Credit Card Network Channel Electronic Signature Active Rule South China Morning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Joseph Fong
    • 1
  • San Kuen Cheung
    • 1
  • Irene Kwan
    • 2
  1. 1.Department of Computer ScienceCity University of Hong KongKowloonHong Kong
  2. 2.Department of Information SystemsLingnan UniversityTuen Mun, N.T.Hong Kong

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