Pace University Biometric Systems

Over the last eight years Seidenberg's School of CSIS at Pace University has developed robust biometric systems for identification (one-of-n response) and for authentication (accept/reject response). In the early years we worked primarily on the identification problem, while in recent years we focused more on the authentication problem.

Pace University Biometric System (PBS)

Although used primarily for keystroke biometric studies, the backend of the system is a robust generic system that can be used for any biometric feature input, and we refer to this system as the Pace University Biometric System (PBS). We have used PBS for keystroke, mouse, stylometry (forensic authorship), and voice biometrics.

Pace University Keystroke Biometric System (PKBS)

Combining PBS with the keystroke frontend yields the Pace University Keystroke Biometric System (PKBS). This system is currently the best in existence, as far as we can determine, and we strongly desire to maintain our leadership in this area. While there are several commercial keystroke biometric systems that operate on passwords, a few seconds of input, our system operates on arbitrary text input of longer duration, usually minutes, and can therefore capture more robust statistical-based features.

Other Pace University Biometric Systems

As we develop other biometric systems using the same backend component, PBS, we name them similarly. For example, combining PBS with a stylometry frontend yields the Pace University Stylometry Biometric System (PSBS), or combining PBS with a mouse movement frontend yields the Pace University Mouse Biometric System (PMBS).

Motivation

There are several interesting applications of this work with related funding opportunities.

  1. The 2008 United States Higher Education Opportunity Act requires institutions of higher learning to make greater online access control efforts by adopting ubiquitous identification technologies, for example to verify the identity of students taking online tests.
  2. The Department of Defense through DARPA's "Active Authentication" project wants to detect intruders by continually authenticating users of all government machines.
  3. NIST is interested in solving the general problem of trusted identities in cyberspace, such as verifying the identity of customers making online transactions.
  4. Similar to NIST, NSF through their "Secure and Trustworthy Cyberspace (SaTC)" project is interested in finding unique, secure, efficient, easy-to-use, and interoperable online identity solutions for accessing online services.
While all three applications are similar in terms of authenticating the user, faster discovery is required in the first two to prevent significant harm.

Primary references on PBS and PKBS
  1. J.V. Monaco, N. Bakelman, S. Cha, and C.C. Tappert, Recent Advances in the Development of a Keystroke Biometric Authentication System for Long-Text Input, Proc. 2013 European Intelligence and Security Informatics Conference, Sweden, August 2013.
  2. N. Bakelman, J.V. Monaco, S. Cha, and C.C. Tappert, Keystroke Biometric Studies on Password and Numeric Keypad Input, Proc. 2013 European Intelligence and Security Informatics Conference, Sweden, August 2013.
  3. C.C. Tappert, S. Cha, M. Villani, and R.S. Zack, Keystroke Biometric Identification and Authentication on Long-Text Input, Int. Journal Information Security and Privacy (IJISP), 2010.
References on Pace University Stylometry Biometric System (PSBS)
  1. J.V. Monaco, J.C. Stewart, S. Cha, and C.C. Tappert, Behavioral Biometric Verification of Student Identity in Online Course Assessment and Authentication of Authors in Literary Works Proc. IEEE Sixth Int. Conf. Biometrics, Washington D.C., October 2013.
  2. J.C. Stewart, J.V. Monaco, S. Cha, and C.C. Tappert, An Investigation of Keystroke and Stylometry Traits for Authenticating Online Test Takers, Proc. IEEE Int. Joint Conf. Biometrics, Washington D.C., October 2011.
Additional References
  1. J.V. Monaco, N. Bakelman, S. Cha, and C.C. Tappert, Developing a Keystroke Biometric System for Continual Authentication of Computer Users, Proc. 2012 European Intelligence and Security Informatics Conference, Denmark, August 2012.
  2. R.S. Zack, C.C. Tappert, and S. Cha, Performance of a Long-Text-Input Keystroke Biometric Authentication System Using an Improved k-Nearest-Neighbor Classification Method, Proc. IEEE 4th Int. Conf. Biometrics, Washington D.C., September 2010.
  3. C.C. Tappert, M. Villani, and S. Cha, Keystroke Biometric Identification and Authentication on Long-Text Input, pp 342-367, Chapter 16 in Behavioral Biometrics for Human Identification: Intelligent Applications, Edited by Liang Wang and Xin Geng, Medical Information Science Reference, 2010.