Killing the Password via Gesture Recognition
We are living in times where we still have to type the password. NeoEyed's gesture recognition is able to detect swipes to authenticate the user to provide access to the mobile. This is a non-trivial problem as many users can have similar gestures. It is important that the classifiers are able to detect fine changes between many users who could potentially break into the phone. We shall talk about how various classifiers are used for such a detection. We shall talk about classifiers such as one-class SVM, multi-level robust classifiers which are useful for this scenario. Our detection mechanism won us the "Paypal Award". We are now building the next generation authentication system for which we shall discuss the technologies and challenges that need to be resolved.
The talk shall be organized as:
1. The problem we are trying to solve. 3
2. What classifiers help in such a scenario. 10
3. Challenges in existing out of box methods 3.
4. What directions are helping us. 4
Outline/Structure of the Talk
We shall discuss our approaches, wins and disadvantages of using various types of classifiers.
Attendees shall learn what type of classifiers are applicable to which scenario and the overall user authentication problem.
Those intending to look at ML applications, specifically interested in classifiers.
Prerequisites for Attendees
Those with ML basics.