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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM40604

Fraud Shield: Leveraging AI for Enhanced Currency Fraud Detection

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM40604

Volume:

9 |

1 |

Jan 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM40604

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

MSA

Mr. Suhail Ashraf

SA

Sehar Altaf

SS

Simran Shafi

MuN

Mehr un Nisa

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Abstract

Counterfeiting is a serious issue in India, with Fake Indian Currency Notes (FICN) posing a persistent challenge. Agencies like the Ministry of Home Affairs’ FCORD are actively addressing it. Advances in technology have worsened the problem, making detection crucial. We propose a deep learning solution using the Xception Architecture to quickly and accurately identify counterfeit rupee notes, safeguarding India’s currency system.

KEYWORDS

Convolutional Neural Network Deep Learning Xception Architecture

Cite This Article

Mr. Suhail Ashraf, Sehar Altaf, Simran Shafi, Mehr un Nisa, "Fraud Shield: Leveraging AI for Enhanced Currency Fraud Detection," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 1, Jan 2025. https://doi.org/10.55041/IJSREM40604

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Publication Date

7/31/2025

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Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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