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Creation And Verification Of Paper Based Certificates With Signatures

1770 words - 8 pages

CREATION AND VERIFICATION OF THE PAPER BASED CERTIFICATES WITH SIGNATURE.

Creation of Signature on the issuing Certificate

According to Murthy et al. (2011), the vital information that has to input in this paper such as Unique no, Reg no, first name, middle name, last name, Father’s name, passing year and obtained marks) need to be considered as an input m. Then after, m is hashed with a secure hashing algorithm (SHA-1) to create a hash value md. The hash value md is then encrypted using the issuing authority private key and the digital signature is found to be encrypted value (ds). Ultimately, ds is converted into a barcode BC and then printed along with the information required on the ...view middle of the document...

However, here Khanna et al. (2006) used flatbed scanners to identify forged areas in images. The methodology used here is based mainly statistical features obtained of imaging sensor pattern used as a fingerprint for the scanner. The use of anisotropic local Polynomial estimator is mainly to obtain noise patterns. On the hand, SVM classifier is mainly used for features of pattern noise for classifying smaller blocks of an image. The feature vector based approach is mainly used to identify forged areas with precision and high accuracy.

In recent years, there were lots of methods developed for the detection of image forgeries.
Despite the fact that each of these techniques are pointed at identifying a specific sort of fraud or are appropriate just for specific classes of pictures, together they structure a great gathering which could be effectively utilized for detection of forged items in extensive variety of situations. For example, a technique dependent upon color filter array (CFA) addition antiques cannot be utilized for scanned images which are created without utilizing CFA.Forgery detection systems dependent upon discovering hints of resampling may have restricted applicability for JPEG pictures. The statistical characteristics of leftover noise and neighborhood prediction errors are utilized for picture treating identification and steganalysis. This algorithm distinguishes pictures that have experienced average filtering, media filtering, rotation, re-sampling, gamma correction, noise addition and image sharpening as altered pictures, which may not be attractive much of the time if these operations are carried out on complete pictures that protect the picture content.

According to Khanna et al. (2006), Pattern noise has been effectively utilized for source camera identification. In pattern noise for a specific digital camera is evaluated by averaging noise relating to various pictures caught from that camera. The method that is utilized is a wavelet channel to gauge the sensor commotion in an image. An enhanced system for source camera identification dependent upon joint estimation and discovery of the camera photograph reaction non-consistency (PRNU) in pictures is displayed. This is utilized in for forgery detection within computerized digital pictures.

Fingerprinting Blank Paper Using Commodity Scanners

On the other hand according to Clarkson et al. (2009) presented a technique used for the authentication of physical documents at random, which therefore shows eventually that there is natural imperfections in the paper texture. The reason why Clarkson et al. (2009) presented this technique is that to demonstration how many forged documents is there circulating. Moreover, it had been difficult to authenticate the content printed on a particular page. However, for some documents such as tickets and currency, it matters not only that the documents has been tampered but also remain that the document is genuine rather than a...

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