# Passwordless Authentication Using a Combination of Cryptography, Steganography, and Biometrics
## 2 Related Work  
Our comprehensive review of past literature relevant to our research topic was already conducted in a recent publication [1]; we have provided the key summary of findings in this section to provide context. Our review paper (RP) identified persistent gaps in the literature related to, and practical implementation of, passwordless authentication schemes. The RP started with an examination of the work by [PERSON] et al. [2] that identified a set of benefits expected of an ideal passwordless system. In their work, [PERSON] et al. submitted that \"replacing passwords with any of the schemes examined is not a question of giving up an inferior technology for something unarguably better, but of giving up one set of compromises and trade-offs in exchange for another\" [2]. The RP then examined other proposals put forward between the period after [PERSON] et al. 's work and 2023, using the same benchmark for evaluation but adjusting for technological innovations that would make possible some of the proposals that were not feasible during the period under consideration by [PERSON] et al. Works by [PERSON] et al. [3] and [PERSON] et al. [4] were identified by the RP as those that offered the most promising results for actually going passwordless. However, the gaps in their schemes suggested that more research was necessary for the schemes to be reliably deployed on a large scale in a practical sense. The contributions of all the previous authors have thus shaped our understanding of the challenges with the development of passwordless authentication. Our RP provides crucial background and should be consulted for a more thorough framing of prior scholarship. Therefore, the most relevant findings identified from assessing the prior literature in the RP have been briefly highlighted in this section as they pertain to the focus of the current research. Most of the behavioural biometrics schemes we identified up to the year 2020 involve some conscious action by the user. However, the human brain has also been observed to produce (unconscious) unique identification data in the form of electrical signals that can be captured using non-invasive means [5]. Based on this, brain-based authentication was proposed by [PERSON] et al. (2021) [6] as a secure method of user authentication. In this scheme, the user's brain signals are captured and processed using machine learning models to extract features that are stored for use during authentication. One limitation of this authentication system is the initial enrolment process; this activity will be carried out in a controlled environment, with qualified personnel managing the procedure in a clinical fashion. Alternatively, users would be required to wear special headgear under strict guidelines. In view of this, further research work is necessary if brain signals are viable as a replacement for passwords. Another biometric feature that is unique is the iris (a part of the human eye), such that \"even the two eyes of an individual and identical twins possess uncorrelated pat terns\" [7], and was the basis of the authentication system proposed by [PERSON] and [PERSON], (2022) [8]. While iris-based systems have been recorded to have the highest degree of accuracy of all biometrics, implementing them as a password alternative requires extensive research. Take the enrolment process, for instance: \"A specialised camera, typically within three feet of the subject, uses an infrared imager to illuminate the eye and capture an extremely high-resolution photograph\" [6]. Unless current devices are upgraded with the capability for such functionality or future devices engineered for this purpose, enrolment will have to be conducted in conditions like that of brain-signal authentication, making it infeasible for mass adoption. Continued research into biometric authentication was reflected in the work of [PERSON] et al. (2022) [9] when they proposed the fusion of multiple behaviours.