# Two-Factor Authentication Scheme for Mobile Money: A Review of Threat Models and Countermeasures
## 4 Results and Discussion  
Through the literature analysis, the threat models below were identified and discussed. Attacks against privacy: In this attack, adversaries infringe on the privacy of mobile money users, agents, MNO, and the MMS. They also compromise the PINs of the subscribers so that the attacker can use them to illegally access the financial details of the victim and perform illicit transactions. Additionally, attackers take advantage of the illiteracy of mobile money users and agents to access their mobile money PINs and accounts. To deal with this attack, [71, 106] proposed a hybrid cryptographic method on the basis of the MD5 algorithm and the RSA algorithm. [PERSON] and [PERSON] [66] and [PERSON], [PERSON], and [PERSON] [70] suggested ECDSA for digital signature and ECIES using AES-GCM as the encryption algorithm. [PERSON] [47] recommended general data privacy legislation and sector-specific laws that protect privacy. Moreover, digital communications law and user regulations in mobile money provide data privacy, confidentiality, and lawful interception. Impersonation attacks: An attacker can assume the identity of a legitimate mobile money user or agent, access the financial details of a registered user, and perform fraudulent transactions. There are 14 authentication protocols [56, 66, 67, 68, 69, 70, 72, 77, 81, 87, 88, 102, 103, 105] to prevent impersonation attacks. The schemes in [81, 105] employed fingerprint biometrics. [PERSON] and [PERSON] [66], [PERSON], [PERSON], and [PERSON] [68], and [PERSON] and [PERSON] [69] used elliptic curve cryptosystems. [PERSON] and [PERSON] [87], [PERSON] and [PERSON] [67], [PERSON], [PERSON], and [PERSON] [56], [PERSON] et al. [77], and [PERSON], [PERSON], and [PERSON] [70] adopted hashing functions. [PERSON], [PERSON], and [PERSON] [72] proposed an asymmetric encryption function. The idea of mutual authentication was proposed in [72, 88]. On the other hand, [102, 103] used random values like OTP. Replay attack: An attacker eavesdrops on network communication between the mobile money user and MMS, and intercepts the data packets that include the PIN, and then delays and resends it to the recipient. To thwart this attack, [66, 68, 69, 102, 103] employed pairing-based cryptography and timestamps in encrypted data. [PERSON], [PERSON], and [PERSON] [56] and [PERSON], [PERSON], and [PERSON] [70] adopted techniques with hashing functions. [PERSON] et al. [77] proposed the use of a one-time username to secure the system against this attack. Masquerade attack: This is where an adversary uses social engineering techniques to obtain the subscribers' SIM card, PIN, or other credentials of the authorised users and uses them to request money from legitimate user's friends and relatives and to carry out illegal business. To resist masquerade attacks, [66, 68, 69] proposed deploying the elliptic curve cryptosystem. [PERSON], [PERSON], and [PERSON] [72] and [PERSON] et al. [88] adopted mutual authentication  
Figure 7: Summary of the number of research papers reviewed. techniques. [PERSON] and [PERSON] [67], [PERSON], [PERSON], and [PERSON] [56], [PERSON] and [PERSON] [71], [PERSON] et al. [77], and [PERSON], [PERSON], and [PERSON] [70] used the idea of hash functions. [PERSON] and [PERSON] [78], [PERSON] and [PERSON] [105], [PERSON] and [PERSON] [81], [PERSON] [80], and [PERSON] 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. The poor protection offered to most mobile money applications and systems allows the attackers to hack and control the systems. Security against this attack was ensured in [68; 80; 81; 89; 104; 105; 107] by using biometric authentication. [PERSON], [PERSON], and [PERSON] [72] and [PERSON] et al. [88] used mutual authentication techniques.