Paradigm shift in document related frauds: Characteristics identification for development of a non-destructive automated system for printed documents

Gupta, Gaurav; Mazumdar, Chandan; Rao, M. S.; Bhosale, R. B.

doi:10.1016/j.diin.2006.01.009

Cited by 13 publications

(3 citation statements)

References 6 publications

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“…Several automated methods have been developed to identify counterfeit documents. Gupta et al [6] have identified several characteristics of printed documents that distinguish them from genuine documents. They discovered that the unique color count in a printed document is much larger than that in a genuine document.…”

Section: Related Workmentioning

confidence: 99%

Detecting Fraudulent Bank Checks

Chhabra¹,

Gupta²,

Gupta³

et al. 2017

Advances in Digital Forensics XIII

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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Section: Related Workmentioning

confidence: 99%

Detecting Fraudulent Bank Checks

Chhabra¹,

Gupta²,

Gupta³

et al. 2017

Advances in Digital Forensics XIII

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“…The importance of documents has driven criminals to perpetrate a number of digitized document frauds. Document frauds involve manufacturing, counterfeiting, altering, selling and/or misusing documents for criminal purposes [4,5]. Indeed, document frauds have become a global problem that requires serious attention on the part of digital forensic researchers and investigators.…”

Section: Introductionmentioning

confidence: 99%

Detecting Data Leakage from Hard Copy Documents

Nayak¹,

Singh²,

Chhabra³

et al. 2018

Advances in Digital Forensics XIV

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Document fraud has evolved to become a significant threat to individuals and organizations. Data leakage from hard copy documents is a common type of fraud. This chapter proposes a methodology for analyzing printed and photocopied versions of confidential documents to identify the source of a leak. The methodology incorporates a novel font pixel manipulation algorithm that embeds data in the pixels of certain characters of confidential documents in a manner that is imperceptible to the human eye. The embedded data is extracted from a leaked printed or photocopied document to identify the specific document that served as the source. The embedded data is robust in that it can withstand errors introduced by printing, scanning and photocopying documents. Experimental results demonstrate the efficiency, robustness and security of the methodology.

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“…One of the earliest approaches was proposed by Gupta, et al [3], who focused on fake documents produced using scanners and printers. In particular, they discovered that a fake document has more unique colors than its genuine counterpart.…”

Section: Detecting Counterfeit Documentsmentioning

confidence: 99%

Detecting Counterfeit Currency and Identifying Its Source

Sarkar

Verma

Gupta

2013

Advances in Digital Forensics IX

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Counterfeit currency varies from low quality color scanner/printer-based notes to high quality counterfeits whose production is sponsored by hostile states. Due to their harmful effect on the economy, detecting counterfeit currency notes is a task of national importance. However, automated approaches for counterfeit currency detection are effective only for low quality counterfeits; manual examination is required to detect high quality counterfeits. Furthermore, no automatic method exists for the more complex -and important -problem of identifying the source of counterfeit notes. This paper describes an efficient automatic framework for detecting counterfeit currency notes. Also, it presents a classification framework for linking genuine notes to their source printing presses. Experimental results demonstrate that the detection and classification frameworks have a high degree of accuracy. Moreover, the approach can be used to link high quality fake Indian currency notes to their unauthorized sources.

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Paradigm shift in document related frauds: Characteristics identification for development of a non-destructive automated system for printed documents

Cited by 13 publications

References 6 publications

Detecting Fraudulent Bank Checks

Detecting Fraudulent Bank Checks

Detecting Data Leakage from Hard Copy Documents

Detecting Counterfeit Currency and Identifying Its Source

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