A Stable and Secure One-Time-Password Generation Mechanism using Fingerprint Features

Abstract

The growth of online application used for financial transactions and transferring personal information is increasingly common on internet and in mobile communication. These applications require authenticating legitimate users by assigning digital identities. Static passwords are perhaps most common type of credentials used today to authenticate the users. To avoid tedious task of remembering passwords, users often behave less securely by using low entropy and weak passwords, thus presenting security threats to online services. Various solutions have been provided to eliminate the need of users to create and manage passwords’ typical solution is based on generating one time password (OTP) for a single session or transaction. Unfortunately in most of the general mechanisms used for generating one time password (OTP) randomness of OTP system breaks after certain period of time and hence passwords become predictable. To solve this problem, in this paper a novel OTP generation method has been proposed, which generates OTP from fingerprint features of the user. The OTP produced from the system is secure as it uses fingerprint features in the seed and RIPEMD160 hash function in OTP generation procedure.

A novel OTP based tripartite authentication scheme

“…The analysis shows that a more significant part of the OTP computation procedures depends on time synchronization, numerical calculations to generate one-time passwords. The arbitrariness of these OTP frameworks breaks after a timeframe and consequently, passwords become foreseeable (Choi and Kwon, 2015; Lone and Mir, 2019).…”

“…The analysis shows that a more significant part of the OTP computation procedures depends on time synchronization, numerical calculations to generate one-time passwords. The arbitrariness of these OTP frameworks breaks after a timeframe and consequently, passwords become foreseeable (Choi and Kwon, 2015; Lone and Mir, 2019). Weak password generation methods, such as MD5, AES, SHA-1 and others, are used in most authentication schemes (Alzomai, 2010; Deore and Waghmare, 2016), leaving them vulnerable and struggling to help on time owing to technical advances.…”

“…The study proposes several methods for detecting singular points using an orientation field image. In the proposed analysis, Poincare Index Method is used, a common and realistic method for recognizing these points from a fingerprint (Magalhães et al , 2009; Li et al , 2013; Iwasokun and Akinyokun, 2014; Lone and Mir, 2019). An input image of the fingerprint must first be converted into an orientation field before the Poincare Index Method can be applied to it.…”

“…Possession: what an individual possesses, such as keys, passports and smart cards. Biometrics: Physiological and behavioral characteristics of a person such as fingerprints, iris, signature, voice, are unique and differentiates one person from another (Zulkarnain et al , 2013; Lone and Mir, 2019). Authentication methods based on possession and knowledge are the most widely used methods for computers, the internet and email accounts.…”