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FRONT-END SIGNATURE COMPARISON ON A CREDIT CARD The purpose of this study was to determine whether it was possible to compare your signature captured upon swiping a credit card to a stored signature on the card itself. Nathan Record, Matthew Richardson, Jarad Shannon, Kevin O'Connor, Dr. Stephen Elliott OVERVIEW INITIAL IDEA EXPERIMENT DESIGN Credit card fraud is an area where literally tens of billions of dollars each year are lost. While a lot of this fraud occurs online, a significant portion also occurs in brick and mortar sites. The method that we designed could be used to help create a first line of deterrence for signature fraud, by catching fraudulent signatures before the transaction would even be posted. Magnetic strip cards have tracks and the third track is not used for card data. Our goal was to develop an application which would allow the storage of a baseline signature template onto the third track of a card, and could compare a live signature at the point of sale to provide preliminary identity verification. Capture signature. Create signature string. Verify signature string can fit onto magnetic stripe card. Capture secondary signature. Compare signatures using Levenshtein distance. Display confidence for comparison(Acts as a tolerance) Note: The iPad was used as a signature capture medium for ease of writing a signature. RESULTS FUTURE WORK There are several opportunities for future work on this project. Using a different signature comparison algorithm could prove useful. Including data about the time it took to sign, as well as the overall signature size would also be an improvement. CONCLUSION The comparison of two signatures was possible in a fast, efficient manner and was capable of being stored on a magnetic stripe card. We also found that a confidence interval of 75 and higher was a strong rating. Anything below 70 is dissimilar and would be rejected. Levenshtein Distance is the minimum number of single-character edits required to turn one string into another. Baseline Comparison Results Good Result Bad Result Data stored on card with signature template on Track 3.

(Spring 2013) Front-end Signature Comparison on a Credit Card

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The purpose of this study was to determine whether it was possible to compare your signature captured upon swiping a credit card to a stored signature on the card itself.

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Page 1: (Spring 2013) Front-end Signature Comparison on a Credit Card

FRONT-END SIGNATURE COMPARISON ON A CREDIT CARD

The purpose of this study was to determine whether it was possible to compare your signature captured upon swiping a credit card to a stored signature on the

card itself.

Nathan Record, Matthew Richardson, Jarad Shannon, Kevin O'Connor, Dr. Stephen Elliott

OVERVIEW

INITIAL IDEA EXPERIMENT DESIGN Credit card fraud is an area where literally tens of billions of dollars

each year are lost. While a lot of this fraud occurs online, a significant

portion also occurs in brick and mortar sites. The method that we

designed could be used to help create a first line of deterrence for

signature fraud, by catching fraudulent signatures before the

transaction would even be posted. Magnetic strip cards have tracks

and the third track is not used for card data. Our goal was to develop

an application which would allow the storage of a baseline signature

template onto the third track of a card, and could compare a live

signature at the point of sale to provide preliminary identity

verification.

• Capture signature.

• Create signature string.

• Verify signature string can fit onto magnetic stripe card.

• Capture secondary signature.

• Compare signatures using Levenshtein distance.

• Display confidence for comparison(Acts as a tolerance)

Note: The iPad was used as a signature capture medium for ease of writing a signature.

RESULTS

FUTURE WORK

There are several opportunities for future work on this project. Using a different signature comparison

algorithm could prove useful. Including data about the time it took to sign, as well as the overall

signature size would also be an improvement.

CONCLUSION

The comparison of two signatures was possible in a fast, efficient

manner and was capable of being stored on a magnetic stripe card.

We also found that a confidence interval of 75 and higher was a

strong rating. Anything below 70 is dissimilar and would be rejected.

Levenshtein Distance is the minimum number of single-character

edits required to turn one string into another.

Baseline

Comparison

Results

Good Result Bad Result

Data stored on card with

signature template on

Track 3.