| 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 == |
| 13 | |
| 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. |