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Speech based OTP system to prevent shoulder surfing.

Bava, Anmol Geer (2020) Speech based OTP system to prevent shoulder surfing. Masters thesis, Dublin, National College of Ireland.

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Abstract

Nowadays authentication schemes are being introduced with additional schemes to the traditional password based authentication systems. Additional schemes include passphrases, token based one- time passwords, token based cards, graphical based systems, and other biometric based schemes. Even with the introduction of new layers of security in authentication schemes, human beings still are the weakest link to even the most secure authentication systems. Although many social engineering techniques can be used to crack an authentication scheme, the most effective and easiest to implement is the shoulder surfing attack. The proposed scheme reduces the probability of shoulder surfing, bruteforce and keylogger based attacks significantly. The paper proposes a novel approach of speech recognition to the traditional otp based system which increases the usability as well as the security of the otp scheme. Although there have been many speech recognition modules produced, the proposed system comprises of the Google Speech recognition module which perfectly fits the requirements of the proposed authentication scheme.
Keywords: Authentication, Speech Recognition, Shoulder surfing, Key logging, OTP

Item Type: Thesis (Masters)
Subjects: 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: Dan English
Date Deposited: 26 Jan 2021 14:26
Last Modified: 26 Jan 2021 14:26
URI: http://norma.ncirl.ie/id/eprint/4487

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