Trust Profiling to Enable Adaptive Trust Negotiation in Mobile Devices

Research Mentor: Steven Demurjian

Graduate Mentor: Eugene Sanzi

Focusing on using credentials  (extended, dynamic, attributes, etc.) to build up a profile for a user that accesses a group of systems and has established a pattern of access and permissions over time.   A trust profile that contains a proof of history of successful access to sensitive data to facilitate identification and authentication for adaptive trust negotiation. The trust profile consists of a set of X.509 identity and attribute certificates, where a certificate is added whenever a user via a mobile application makes a successful attempt to request data from a server where no relationship between the user and server has previously existed as a result of trust negotiation. The work will be incorporated into the Connecticut Concussion Tracker mobile application. The Connecticut Concussion Tracker (CT2) application that has been developed as a joint effort between the Depts of Physiology and Neurobiology, and Computer Science & Engineering at the University of Connecticut, in collaboration with faculty in the Schools of Nursing and Medicine in support of a newly passed law on concussions to be tracked K12 (

Components for Student Participation Research tasks for REU participants will include learning about secure mobile computing from the user side (access control models, delivering custom content to users, and adaptive certification). Project supervisors along with senior graduate students will work closely with the REU students and provide mentorship.