Deception analysis using Mouse tracking Agrim Gupta.
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Transcript of Deception analysis using Mouse tracking Agrim Gupta.
![Page 1: Deception analysis using Mouse tracking Agrim Gupta.](https://reader030.fdocuments.us/reader030/viewer/2022033017/5697bfd01a28abf838caa926/html5/thumbnails/1.jpg)
Deception analysis usingMouse tracking
Agrim Gupta
![Page 2: Deception analysis using Mouse tracking Agrim Gupta.](https://reader030.fdocuments.us/reader030/viewer/2022033017/5697bfd01a28abf838caa926/html5/thumbnails/2.jpg)
Basics
• People hesitate when lying• This shows up in their body movements• Polygraphs measure impulses• Mouse tracking measures the entire flow• This is much difficult to understand than a
simple polygraph• Mouse tracking is economical too
![Page 3: Deception analysis using Mouse tracking Agrim Gupta.](https://reader030.fdocuments.us/reader030/viewer/2022033017/5697bfd01a28abf838caa926/html5/thumbnails/3.jpg)
The experiment
• Two sets of 14-15 ‘obvious’ questions• Participants are made to sit in front of a
computer, made to answer with a mouse• One set is truthfully answered, the
participant lies in the other one• Participant is not told the objective of the
experiment until its done
![Page 4: Deception analysis using Mouse tracking Agrim Gupta.](https://reader030.fdocuments.us/reader030/viewer/2022033017/5697bfd01a28abf838caa926/html5/thumbnails/4.jpg)
MouseTracker Designer
![Page 5: Deception analysis using Mouse tracking Agrim Gupta.](https://reader030.fdocuments.us/reader030/viewer/2022033017/5697bfd01a28abf838caa926/html5/thumbnails/5.jpg)
MouseTracker Analyzer
![Page 6: Deception analysis using Mouse tracking Agrim Gupta.](https://reader030.fdocuments.us/reader030/viewer/2022033017/5697bfd01a28abf838caa926/html5/thumbnails/6.jpg)
Highlights
• Questions are randomized• Choice for truth-set or lie-set is random• Individual and Global calibration curve give
greater flexibility in analysis• Mouse tracking has better potential of being
accurate as people are comfortable with it
![Page 7: Deception analysis using Mouse tracking Agrim Gupta.](https://reader030.fdocuments.us/reader030/viewer/2022033017/5697bfd01a28abf838caa926/html5/thumbnails/7.jpg)
X-Deception Curve
![Page 8: Deception analysis using Mouse tracking Agrim Gupta.](https://reader030.fdocuments.us/reader030/viewer/2022033017/5697bfd01a28abf838caa926/html5/thumbnails/8.jpg)
Y-Deception Curve
![Page 9: Deception analysis using Mouse tracking Agrim Gupta.](https://reader030.fdocuments.us/reader030/viewer/2022033017/5697bfd01a28abf838caa926/html5/thumbnails/9.jpg)
Full Deception Curve (UF)
![Page 10: Deception analysis using Mouse tracking Agrim Gupta.](https://reader030.fdocuments.us/reader030/viewer/2022033017/5697bfd01a28abf838caa926/html5/thumbnails/10.jpg)
Full Deception Curve (F)
![Page 11: Deception analysis using Mouse tracking Agrim Gupta.](https://reader030.fdocuments.us/reader030/viewer/2022033017/5697bfd01a28abf838caa926/html5/thumbnails/11.jpg)
Drawbacks
• One-sided questions – software limitation• Test can be easily faked• Some questions may have doubtful answers• Different people have different mouse
movement expertise• Questions need more variety and need to be
more in number
![Page 12: Deception analysis using Mouse tracking Agrim Gupta.](https://reader030.fdocuments.us/reader030/viewer/2022033017/5697bfd01a28abf838caa926/html5/thumbnails/12.jpg)
Scope for Improvement
• A better software that allows more flexibility and is more stable
• Additional support from eye-tracking data• Clarity in questions needed• A standard desk with standard mouse
support can be arranged for• Questions should have randomized
placements of options
![Page 13: Deception analysis using Mouse tracking Agrim Gupta.](https://reader030.fdocuments.us/reader030/viewer/2022033017/5697bfd01a28abf838caa926/html5/thumbnails/13.jpg)
Thank You