| | 1 | [[TOC(Other/Summer/2021/MobileUserAuthenticationViaDeepLearning/*, depth=1, heading=Mobile User Authentication Via Deep Learning)]] |
| | 2 | |
| | 3 | = Mobile User Authentication Via Deep Learning = |
| | 4 | **WINLAB Summer Internship 2021** |
| | 5 | |
| | 6 | **Group Members:** Aditi Satish, Daniel Liu, Sharad Prasad, Emily Gao, David Man |
| | 7 | |
| | 8 | == Project Website == |
| | 9 | |
| | 10 | [https://sites.google.com/view/mobileuserauthentication] |
| | 11 | |
| | 12 | == Project Objective == |
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| | 14 | By using wireless signals as input, we can develop deep learning techniques to extract unique behavioral biometrics to perform user authentication in real-time. |
| | 15 | |
| | 16 | Objectives: |
| | 17 | |
| | 18 | * Use of Wifi signals to capture inherited behavioral characteristics to facilitate identification/authentication. |
| | 19 | |
| | 20 | * Environment Dependent Solution (Robust to Placement). |
| | 21 | |
| | 22 | * To examine CSI of Wifi to study behavioral characteristics. |
| | 23 | |
| | 24 | * Develop a CNN model resilient to spoofing attacks. |