RETRACTED: Verification of pattern unlock and gait behavioural authentication through a machine learning approach
International Journal of Intelligent Unmanned Systems
ISSN: 2049-6427
Article publication date: 5 January 2021
Issue publication date: 7 January 2022
Retraction notice
The publishers of International Journal of Intelligent Unmanned Systems wish to retract the article Chaitanya, G.K. and Raja Sekhar, K. (2022), “Verification of pattern unlock and gait behavioural authentication through a machine learning approach”, International Journal of Intelligent Unmanned Systems, Vol. 10 No. 1, pp. 48-64. https://doi.org/10.1108/IJIUS-09-2020-0048 An internal investigation into a series of submissions has uncovered evidence that the peer review process was compromised. As a result of these concerns, the findings of the article cannot be relied upon. This decision has been taken in accordance with Emerald’s publishing ethics and the COPE guidelines on retractions.
The publishers of the journal sincerely apologize to the readers.
Abstract
Purpose
The existing authentication procedures (pin, pattern, password) are not very secure. Therefore, the Gait pattern authentication scheme is introduced to verify the own user. The current research proposes a running Gaussian grey wolf boosting (RGGWB) model to recognize the owner.
Design/methodology/approach
The biometrics system plays an important role in smartphones in securing confidential data stored in them. Moreover, the authentication schemes such as passwords and patterns are widely used in smartphones.
Findings
To validate this research model, the unauthenticated user's Gait was trained and tested simultaneously with owner gaits. Furthermore, if the gait matches, the smartphone unlocks automatically; otherwise, it rejects it.
Originality/value
Finally, the effectiveness of the proposed model is proved by attaining better accuracy and less error rate.
Keywords
Citation
Chaitanya, G.K. and Raja Sekhar, K. (2022), "RETRACTED: Verification of pattern unlock and gait behavioural authentication through a machine learning approach", International Journal of Intelligent Unmanned Systems, Vol. 10 No. 1, pp. 48-64. https://doi.org/10.1108/IJIUS-09-2020-0048
Publisher
:Emerald Publishing Limited
Copyright © 2020, Emerald Publishing Limited