Safe Zone

• 

  Landing Page

• 

  Register Page

• 

• 

  Login Page

• 

  Verifying the face, password and most importantly on behavioral characteristic

• 

  Transfer Bitcoin to other account

• 

• 

Inspiration

On top of Physiological Biometrics authentication like Face ID and Finger Size, we have added up another level of Behavioral Biometrics to identifying or verifying the identity of a person based on his behavioral characteristics such as the acceleration of how he is inputting the password, the pressure touch on each button, the gap time to move from one button to another button. Then, based on the biometrics data, observe from the end user, has compared with the existing data, the experience data and do the authentication for either improved or denied. After succeed to validate the person identity, he can perform his internal system freely. The main function, we planned to embedded with our system, is to scan face of other user to pay. Instead of using QR code, we can use the uniqueness of the face as the Primary Key to do the transfer or receiving the money by connecting with Rakuten API.

What it does

Face Recognition, Passcode, and Behavioral characteristics, With these 3 layers model or 3 ways of authentication method, the overall processes are convenience, less time consuming and most importantly, stronger than ever. The user is no longer fear of being attacked or hacked to access into his credential data anymore. During the registration time, it captures the physiological biometrics parameters like face and finger size while in behavioral biometrics collects the pressure touch on the button, the acceleration from to one pin to another, the time gap between one pin to another button and then carry on all of the data and stores it into our database for training and classifier.

How we built it

We have been through a lot of brainstorms, design process, discussions in order to find the suitable algorithms, libraries and workflow to be followed by. With the only 48 hours, we have tried to assemble up and prioritize all the good approaches and ideas to speeding up our work to ensure that we can be finished on time.

Challenges we ran into

To gather up the parameter and dive deep into the each behavioral characteristics are kinda challenging and pretty hard for us since we have no experience with that at all. As the team, we tried to check all the requirements one by one in all kind of perspectives not to be missed or gone error with the main functionality of our system. Many hours of rectifying, bug fixing and requirements checking but still we committed to finish as best as we can.

Accomplishments that we're proud of

We believe that Safe Zone is going to be an important role and part of the future society to help and strengthen up the security of the citizen.

What's next for Safe Zone

As the hackathon is only for 48 hours, we have found and implemented some behavioral characteristics, in practically, in the future surely we can expand and find more parameters to be added to make it bigger so it can proven that it is going to be high security and stronger.

Built With

• azure
• behavioral-recognition
• django
• face-recognitiom
• ios
• knn
• machine-learning
• payment
• rakuten