Mobile Device User Authentication
without Traditional Passcode

Project Description

Smartphone users store a variety of sensitive information and provide access to sensitive functionality. Users can have dozens of passwords to remember for accessing smartphones and sites for online banking, online shopping, and social networking. We have reached the point where we need alternatives to the usual username/password access procedure. Today’s smartphones have many embedded sensors that can be used for unique authentication mechanisms to unlock phones without entering a password. The focus of this project is to investigate such authentication mechanisms and make inroads toward developing a unique one.

Background - Some Interesting Related Developments

Gartner report on mobile device authentication.
Intel unveils in 2015 a Password Manager App that opens sites with user's face.
A Digital Tattoo can unlock a phone.
Nordic Bank has a Typing Behavior App and Your keyboard might know what you're feeling.

Project Plan

Phase 1 - completed Fall 2014: see [1].

Phase 2 - completed Spring 2015: see [2].

Phase 3 - Fall 2015: This phase of the study will build on the results from the work of Spring 2015, and determine how user authentication security can be improved by combining, either in parallel or sequentially, the methods investigated. This is referred to as biometric information fusion.

The data can include, but is not limited to:

Project Deliverables

Faculty and doctoral student Leigh Anne Clevenger advocate working in an Agile format and will guide you in this project development methodology which involves: "frequent delivery of quality product", for example every two weeks, and "do the best you can with what you know now".

Key Project Deliverables

References

  1. Developing a User Identification Mechanism for Secure Mobile Phone Access Replacing the Tedious Username/Password, Javier Castillo, Ashley Haigler, Sara Siddiqui, Mychal Wilson, Leigh Anne Clevenger, and Charles C. Tappert, Proc. Research Day Conference, Seidenberg School of CSIS, Pace University, 2015.
  2. Design and User Acceptability Testing of Secure Mobile Phone Authentication Mechanism Based on Fingerprint Sensing and Geofencing, Sara Siddiqui, Nitish Nandkumar Pisal, Nikhita Gopidi, Nishant Maheshbhai Patel, Tanya Sahin, Shreyansh Shah, Leigh Anne Clevenger, Javid Maghsoudi, John V. Monaco, and Charles C. Tappert, Proc. Research Day Conference, Seidenberg School of CSIS, Pace University, 2015.
  3. Mobile Biometrics - 2014 book excerpts