Handwriting Behaviour Analysis for deception detection using SVM Classifier in virtualized Environment

Abstract

There are various methods in practice to analyze deception by the law enforcing departments. Analyzing handwritten document is still considered to be one of the reliable methods of detecting deception. Handwritten documents are usual and reliable source of communication even in today's scenario. The handwritten text is considered to reflect human's body mind coordination. Researchers state that human behaviour can be analyzed by studying a person's handwriting. The paper consists of studies and implementation of online Handwritten Behaviour Analysis in proxmox-server virtualization Environment. C# language was used to implement the Behaviour Analysis part and python is used to validate the classification accuracy on the collected data. We have extended the previous work to client server mode to highlight the part of online Behaviour analysis to identify the uniqueness in characteristics of any person to differentiate deceptive and true statements. This paper will report the development and deployment of an online virtual server based handwriting behaviour analysis system using SVM based supervised Machine learning algorithm for classification.