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2020-06-01
Mohd Ariffin, Noor Afiza, Mohd Sani, Noor Fazlida.  2018.  A Multi-factor Biometric Authentication Scheme Using Attack Recognition and Key Generator Technique for Security Vulnerabilities to Withstand Attacks. 2018 IEEE Conference on Application, Information and Network Security (AINS). :43–48.
Security plays an important role in many authentication applications. Modern era information sharing is boundless and becoming much easier to access with the introduction of the Internet and the World Wide Web. Although this can be considered as a good point, issues such as privacy and data integrity arise due to the lack of control and authority. For this reason, the concept of data security was introduced. Data security can be categorized into two which are secrecy and authentication. In particular, this research was focused on the authentication of data security. There have been substantial research which discusses on multi-factor authentication scheme but most of those research do not entirely protect data against all types of attacks. Most current research only focuses on improving the security part of authentication while neglecting other important parts such as the accuracy and efficiency of the system. Current multifactor authentication schemes were simply not designed to have security, accuracy, and efficiency as their main focus. To overcome the above issue, this research will propose a new multi-factor authentication scheme which is capable to withstand external attacks which are known security vulnerabilities and attacks which are based on user behavior. On the other hand, the proposed scheme still needs to maintain an optimum level of accuracy and efficiency. From the result of the experiments, the proposed scheme was proven to be able to withstand the attacks. This is due to the implementation of the attack recognition and key generator technique together with the use of multi-factor in the proposed scheme.