Signature Forgery Detection

Bin Ashraf, Anaz (2022) Signature Forgery Detection. Masters thesis, Dublin, National College of Ireland.

Preview	PDF (Master of Science) Download (712kB) | Preview
Preview	PDF (Configuration manual) Download (1MB) | Preview

Abstract

Digital signatures are widely used in recent times by organisations public and private alike. Similar to fingerprints the signatures are legally binding. Another reason why they are being used is that they are easy to handle and store. The digital signatur es are utilised mainly in ecommerce websites for delivery authentication to the customers, bank customer procedures and verification, government organisations and various other businesses big and small. Nowadays, the government uses digital signatures for contracts and verifying documents. When there is an advancement in IT, it has its advantages and disadvantages. Signature is one of the important biometric techniques that may be used for manipulating the signature data and using them for malicious purpos es. Two efficient machine learning algorithms VGG16 and random forest are implemented in the research attempt to identify a way to mitigate the risk caused by signature forgery. The machine language techniques are being trained and tested to check whether the signatures given are original or fake using a data set.

Item Type:	Thesis (Masters)
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Divisions:	School of Computing > Master of Science in Cyber Security
Depositing User:	Clara Chan
Date Deposited:	30 Nov 2022 17:45
Last Modified:	30 Nov 2022 17:45
URI:	https://norma.ncirl.ie/id/eprint/5948

Actions (login required)

View Item