Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/2092
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dc.contributor.authorChandrasekara, P-
dc.contributor.authorAbeywardana, H-
dc.contributor.authorRajapaksha, S-
dc.contributor.authorSanjeevan, p-
dc.date.accessioned2022-04-29T04:15:53Z-
dc.date.available2022-04-29T04:15:53Z-
dc.date.issued2019-07-29-
dc.identifier.citationChandrasekara, P., Abeywardana, H., Rajapaksha, S., Parameshwaran, S., Yapa Abeywardana, K. (2020). Behavior and Biometrics Based Masquerade Detection Mobile Application. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Computing. SAI 2020. Advances in Intelligent Systems and Computing, vol 1230. Springer, Cham. https://doi.org/10.1007/978-3-030-52243-8_32en_US
dc.identifier.isbn978-3-030-52243-8-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/2092-
dc.description.abstractMobile phone has become an important asset when it comes to information security since it has become a virtual safe. However, to protect the information inside the mobile, the manufacturers use the technologies as password protection, face recognition or fingerprint protection. Nevertheless, it is clear that these security methods can be bypassed. That is when the urge of a post-authentication is coming to the surface. In order to protect the phone from an unauthorized or illegitimate user this method is proposed as a solution. The aim of the proposed solution is to detect the illegitimate user by monitoring the behavior of the user by four main parameters. They are: 1) Keystroke dynamics with a customized keyboard; 2) location detection; 3) voice recognition; 4) Application usage. In the initial state machine learning is used to train this mobile application with the authentic user’s behavior and they are stored in a central database. After the initial training period the application is monitoring the usage and comparing it with the already saved data of the user. Another unique feature of this is the prevention mechanism it executes when an illegitimate user is detected. Furthermore, this application is proposed as an inbuilt application in order to avoid the deletion of app or uninstallation of the app by the intruder. With this Application which is introduced as “AuthDNA” will help you to protect the sensitive information of your mobile device in a case of theft and bypassing of initial authentication.en_US
dc.language.isoenen_US
dc.publisherSpringer, Chamen_US
dc.relation.ispartofseriesInternational Conference on Advances in Computing and Technology;pp 446–458-
dc.subjectAuthenticationen_US
dc.subjectBiometricsen_US
dc.subjectMachine learningen_US
dc.subjectMasqueradeen_US
dc.titleBehavior & Bio metric based Masquerade Detection Mobile Applicationen_US
dc.typeArticleen_US
dc.identifier.doi10.1007/978-3-030-52243-8_32en_US
Appears in Collections:Department of Computer Systems Engineering-Scopes
Research Papers - SLIIT Staff Publications



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