Review and Analysis of Mathematical Approaches for Adaptive Authentication using Machine Learning
In today’s technological era, the combined problem of assuring user productivity and maintaining strong security standards has become quite a key challenge. As security considerations, have not to hurt productivity, significant efforts must be taken to achieve such goals. The notion of adaptive authentication comes into play to avoid friction in user experience so that a balance between security and user productivity can be maintained. Traditional authentication frameworks are becoming more obsolete due to their ineffectiveness in incorporating additional risk criteria such as location, network type, and operating system into the authentication management process. Adaptive authentication is a combination of authentication and machine learning (ML) technologies that can help in realizing secure intelligent systems. The goal of this research is to provide a complete review of the current applications of various machine learning algorithms often employed in adaptive authentication techniques. Throughout this study, the advantages, limits, and suggestions for future research will be thoroughly discussed.
Authors
- Ritu Agrawal (ORCID: https://orcid.org/0009-0006-9374-5942)
Publication Details
- Journal
- Communications on Applied Nonlinear Analysis
- Published
- 2024-10-09
- DOI
- https://doi.org/10.52783/cana.v32.1906
- Primary Topic
- Neural Networks and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00