A Proposed Secure Mobile Money Transfer System for SME in Bangladesh: An Industry 4.0 Perspective

Islam, Iyolita; Munim, Kazi Md.; Islam, Muhammad Nazrul; Karim, Md. Fazlul

doi:10.1109/sti47673.2019.9068075

Cited by 14 publications

(29 citation statements)

References 27 publications

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“…Kisore and Sagi [67], Rodrigues, Chaudhari, and More [56], Sharma and Bohra [71], Alhothailya et al [77], and Salim, Sagheer, and Yaseen [70] used the idea of hash functions. Coneland and Crespi [78], Okpara and Bekaroo [105], Sharma and Mathuria [81], Chetalam [80], and Islam et al [89] proposed the use of physiological and behavioural biometrics. Spoofing attacks: An adversary can assume the role of a mobile system administrator and have full access to the system.…”

Section: Resultsmentioning

confidence: 99%

“…PINs are widely used for user authentication such as withdrawing cash from mobile money or withdrawing money from an automated teller machine (ATM) [84]. Mtaho [52], Islam [85], Ombiro [86], Singh and Jasmine [87], Fan et al [88], Islam et al [89], and Zadeh and Barati [90] employed authentication schemes using PINs to verify user identity. Using PINs, the schemes in [86,87,90] provided convenience, efficiency, reliability, and security in mobile transactions.…”

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confidence: 99%

“…Using PINs, the schemes in [86,87,90] provided convenience, efficiency, reliability, and security in mobile transactions. Moreover, the schemes in [52,85,89] used PINs to achieve better dependability and customer satisfaction. The PIN should be easy to remember, random, and hard to guess, while it should be changed frequently, distinct for different accounts, and not written down or stored in plaintext [52].…”

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confidence: 99%

“…The scheme in [90] used facial recognition in authentication to increase the security and reliability of mobile banking systems. Using iris recognition, the scheme in [89] helped to achieve better efficiency, accuracy, dependability, customer satisfaction, and security during mobile money authentication. Moreover, the scheme in [68] employed retina recognition in mobile money authentication to provide security against MITM attack, replay attack, DoS attack, spoofing attack, and repudiation.…”

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confidence: 99%

“…The authentication schemes in [80,86] used voice recognition to increase efficiency, convenience, and security, as well as to resist impersonation attack. [52,81,85,88,104,105] Facial recognition [90] Iris recognition [89] Retina recognition [68] Voice recognition [80,86]…”

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confidence: 99%

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Two-Factor Authentication Scheme for Mobile Money: A Review of Threat Models and Countermeasures

2020

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The proliferation of digital financial innovations like mobile money has led to the rise in mobile subscriptions and transactions. It has also increased the security challenges associated with the current two-factor authentication (2FA) scheme for mobile money due to the high demand. This review paper aims to determine the threat models in the 2FA scheme for mobile money. It also intends to identify the countermeasures to overcome the threat models. A comprehensive literature search was conducted from the Google Scholar and other leading scientific databases such as IEEE Xplore, MDPI, Emerald Insight, Hindawi, ACM, Elsevier, Springer, and Specific and International Journals, where 97 papers were reviewed that focused on the topic. Descriptive research papers and studies related to the theme were selected. Three reviewers extracted information independently on authentication, mobile money system architecture, mobile money access, the authentication scheme for mobile money, various attacks on the mobile money system (MMS), threat models in the 2FA scheme for mobile money, and countermeasures. Through literature analysis, it was found that the threat models in the 2FA scheme for mobile money were categorised into five, namely, attacks against privacy, attacks against authentication, attacks against confidentiality, attacks against integrity, and attacks against availability. The countermeasures include use of cryptographic functions (e.g., asymmetric encryption function, symmetric encryption function, and hash function) and personal identification (e.g., number-based and biometric-based countermeasures). This review study reveals that the current 2FA scheme for mobile money has security gaps that need to be addressed since it only uses a personal identification number (PIN) and a subscriber identity module (SIM) to authenticate users, which are susceptible to attacks. This work, therefore, will help mobile money service providers (MMSPs), decision-makers, and governments that wish to improve their current 2FA scheme for mobile money.

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