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Continuous Authentication of Smartphone Users: Touchscreen interactions

Undergraduate #234
Discipline: Computer Sciences and Information Management
Subcategory: Computer Science & Information Systems
Session: 1
Room: Exhibit Hall A

Jahmelia Atkinson - Fort Valley State University
Co-Author(s): Peng Jiang



Smartphones are drastically evolving, they are equipped with the capabilities of performing intelligent activities like sensing, computing and networking. They allow users to perform a huge range of duties such as, socializing, communicating, storing and having access quick access to personal information. Today, majority of people have a tendency to store exclusive sorts of sensitive assets on their phone. These records may consist of personal Ids, bank account information and other valuable information; Because of this, smartphones are exposed to a slew of security threats and attacks from attackers. Smartphone authentication mechanisms are susceptible to numerous attacks such as smudge attacks, guessing, shoulder-smurfing. To tackle these challenges, we introduce continuous authentication of smartphone users. In this study, we examined how a smartphone user can be recognized based solely on their touchscreen interactions. We examined the touchscreen interactions of 8 different subjects performing distinctive touchscreen gestures. We have created an android application to capture the users unique touch events. For authentication purposes and recognizing a user we proposed a Convolutional Neural Network model using Keras in python. We anticipate this research will help significantly minimize breaches due to unauthorized access to smartphones.

Funder Acknowledgement(s): National Science Foundation and Department of Education

Faculty Advisor: Dr. Masoud Naghedolfeizi, feizim@fvsu.edu

Role: I carried out this research under the supervision of my advisors and with the help of my co-author.

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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