Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource PHD PhD PhD Thesis Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Relation A related resource 61000356 Title A name given to the resource Design and Development of Adaptive Authentication Model to Detect User Behavior Anomalies Subject The topic of the resource Computer Science and Engineering Description An account of the resource The password-based authentication system has recently become more secure as the riskbased authentication system(RBA) is indentured. Recent research in the area has shown the significant use of 2 Factor Authentication (2FA) and Multi-Factor Authentication(MFA) in many commercial applications using Risk Based newlineAuthentication(RBA). The RBA system monitors the parameters extracted during the user login process, and based on the proposed model, the system raises a multi-factor newlineauthentication to the user. As the vulnerability has increased concerning passwords, fingerprints easy access to any web application may result in a security flow; the reason can be the existing methodology of the RBA system and also the unavailability of the data of the users during the initial login process, which hinders the authentication system during the initial login process as there is no standard method to incorporate RBA in the authentication system. Few researchers have proposed novel approaches to improve the authentication system. Still, to the best of our knowledge, no research has suggested methods to address the authentication system during the initial login process and also provide a robust way, a combination of Machine Learning (ML) and statistical newlineapproaches. Hence, a novel method is proposed for the RBA system during the initial newlinelogin phase using a Hierarchical Sub-Feature Based Model -(HSFBM) for different user newlinecategories. The FAR is comparatively better in our proposed model against the standard newlinemodel, with minimal re-authentication requests for the user. Creator An entity primarily responsible for making the resource R M, Pramila Source A related resource from which the described resource is derived Author's Submission Publisher An entity responsible for making the resource available Christ(Deemed to be University) Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Contributor An entity responsible for making contributions to the resource Shukla, Samiksha Rights Information about rights held in and over the resource Open Access Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource PhD Identifier An unambiguous reference to the resource within a given context <a href="http://hdl.handle.net/10603/582387" target="_blank" rel="noreferrer noopener">http://hdl.handle.net/10603/582387</a>