Citation

R. Ganesan, Thinesh (2023) Security and privacy risk assessment in mobile payment services using Analytic Hierarchy Process and Bayesian Network. Masters thesis, Multimedia University.

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Abstract

Mobile payments have observed a significant rise in usage in recent years. According to a survey conducted by the Malaysian Digital Association (MDA) and comScore, the number of mobile payment users in Malaysia increased by 11% in 2020, reaching a total of 6.4 million users. Trust and confidence are crucial factors when it comes to making financial transactions via mobile devices. As a flexible and fast alternative to conventional payment methods such as cash or credit cards, people can now use mobile payments to pay for a wide range of goods and services. Nevertheless, the users have a feeling of fear and unwillingness to take part in a transaction because they are concerned about the privacy and security risks associated with mobile payment. Theft and data loss are common problems that can occur with mobile devices. It is possible for a person to become a victim of payment fraud or personal identity theft if the mobile device is lost by the subject. In this research, an integrated approach for security and privacy analysis based on the Analytic Hierarchy Process (AHP) and Bayesian Network (BN) to increase mobile payment safety has been studied to address the complications and restrictions associated with mobile payment services. The research aims to design a responsive Analytical Hierarchy Process (AHP) Pairwise Comparison framework along with a Bayesian Network developed to elicit expert knowledge for security and privacy risk events and consequences dependencies. AHP ranks and prioritizes alternatives based on multiple criteria, the potential security risks and consequences associated with mobile payment services. The results of AHP are then used as input to the BN model, which captures the probabilistic relationships between different variables and assesses the likelihood of different outcomes.

Item Type:	Thesis (Masters)
Additional Information:	Call No.: QA279.4 .T45 2023
Uncontrolled Keywords:	Statistical decision
Subjects:	Q Science > QA Mathematics > QA273-280 Probabilities. Mathematical statistics
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	28 Aug 2024 08:26
Last Modified:	28 Aug 2024 08:26
URII:	http://shdl.mmu.edu.my/id/eprint/12870

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