Hiding Financial data in applications based on AES Encryption and Steganography Method

Lohani, Parwat (2024) Hiding Financial data in applications based on AES Encryption and Steganography Method. Masters thesis, Dublin, National College of Ireland.

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Abstract

As per NASDAQ Financial crime report, $465.8B are lost to financial crimes in 2023 and organizations are trying to secure and protect their customers data like password, credit card more than ever. With the advancement in hardware and computing infrastructure it is easier to crack encrypted data, hence, this research Paper proposed a detailed implementation of cryptography and steganography together to store customer data without compromising Confidentiality, Integrity and image quality and making it difficult to extract and retrieve. A model was created using Python and tested through METLAB on the public images data set provided by University of Southern California. The approach was, first, encrypt, using AES-256 Bit, the various payloads, ranging from 10K bytes to 80K bytes and ,second, embedding the Payload in the images. The efficacy of the model was tested by analysing the PSNR, MSE, NCC, BER values. The tests showed a decrease in PSNR, indicating successful data hiding and An increase in NCC confirmed that the steganographic images remained visually similar. Based on the results captured from the tests, it can be concluded that approach mentioned in this research paper holds significant potential in the financial market for concealing customer data.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Pantridge, Michael UNSPECIFIED
Uncontrolled Keywords:	Cryptography; Cipher Block Chaining; AES; Steganography; Peak-Signal-to-noise ratio (PSNR); Mean Squared Error (MSE); Normalized Cross-Correlation (NCC); Bit-ErrorRate(BER)
Subjects:	H Social Sciences > HG Finance Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security
Divisions:	School of Computing > Master of Science in Cyber Security
Depositing User:	Ciara O'Brien
Date Deposited:	30 Jul 2025 10:44
Last Modified:	30 Jul 2025 10:44
URI:	https://norma.ncirl.ie/id/eprint/8333

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