Pace University researchers are in the process of creating an interface to Pace’s keystroke biometric authentication system on Moodle, a free source e-learning software platform. The Seidenberg School will pilot the system at Pace in the fall 2013 semester.
FOR IMMEDIATE RELEASE
New research shows keystroke and stylometry biometrics can verify the identity of students in online examination environments
Application becoming more important with the increase in student enrollment of online classes, and growing concerns about security and academic integrity
White Plains, NY – July 29, 2013 – Researchers at Pace University’s Seidenberg School of Computer Science and Information Systems are investigating keystroke and stylometry behavioral biometrics towards developing a robust system to authenticate students taking online examinations.
The researchers are in the process of creating an interface to Pace’s keystroke biometric authentication system on Moodle, a free source e-learning software platform. The Seidenberg School will pilot the system at Pace in the fall 2013 semester.
“The main application of interest in this study is verifying the identity of students in online examination environments, an application that is becoming more important with the student enrollment of online classes increasing, and instructors and administrations becoming concerned about evaluation security and academic integrity,” the researchers write. “The 2008 federal Higher Education Opportunity Act (HEOA) requires institutions of higher learning to make greater access control efforts for the purposes of assuring that students of record are those actually accessing the systems and taking online exams by adopting identification technologies as they become more ubiquitous.
“To meet the needs of this act, the keystroke biometric seems appropriate for the student authentication process. Stylometry appears to be a useful addition to the process because the correct student may be keying in the test answers but a coach could be providing the answers and the student merely typing the coach’s words without bothering to convert the linguistic style into his own.”
Keystroke biometric systems measure typing characteristics believed to be unique to an individual and difficult to duplicate. Stylometry is the study of determining authorship from the authors’ linguistic styles.
The Pace researchers obtained performance statistics on keystroke, stylometry, and combined keystroke-stylometry systems on data from 30 students taking examinations in a university course. They found the performance of the keystroke system was 99.96% and 100.00%, while that of the stylometry system was considerably weaker at 74% and 78%, on test input of 500 and 1000 words, respectively. To further investigate the stylometry system, a separate study on 30 book authors achieved performance of 88.2% and 91.5% on samples of 5000 and 10000 words, respectively, and the varied performance over the population of authors was analyzed.
The research team at Pace includes Vinnie Monaco, an M.S. in computer science student and the primary researcher and programmer for the studies; John Stewart, a recent graduate of Seidenberg’s Doctor of Professional Studies (DPS) program; and Ned Bakelman, a current student in the DPS program. The research was done under the supervision of Professor Charles C. Tappert, Ph.D., the former IBM researcher who spearheaded the development of the handwriting recognizer in IBM’s ThinkPad, and investigated the military potential of wearable computers for Army Research Labs.
About the Pace Keystroke Biometric System (PKBS)
Pace’s Seidenberg School of Computer Science and Information Systems has developed the Pace Keystroke Biometric System (PKBS), which can be used for both identifying and authenticating users via their typing rhythms and patterns through the monitoring and capturing of keyboard events. The researchers say it has the capability to recognize with a “high degree of accuracy” the typing characteristics that are unique to each individual.
A separate new study by the Pace researchers focused on the development and evaluation of a new classification algorithm that halves the previously reported best error rate. Using keystroke data from 119 users, closed system performance was obtained as a function of the number of keystrokes per sample. The researchers found that for each population size, the performance increases, and the equal error rate decreases, as the number of keystrokes per sample increases. Performance on 14, 30, and 119 users was 99.6%, 98.3%, and 96.3%, respectively, on 755-keystroke samples, indicating the potential of this approach.
About Pace University
Since 1906, Pace University has educated thinking professionals by providing high quality education for the professions on a firm base of liberal learning amid the advantages of the New York metropolitan area. A private university, Pace has campuses in Lower Manhattan and Westchester County, NY, enrolling nearly 13,000 students in bachelor’s, master’s, and doctoral programs in its Lubin School of Business, Dyson College of Arts and Sciences, College of Health Professions, School of Education, School of Law, and Seidenberg School of Computer Science and Information Systems.
Media contacts: Bill Caldwell, 212-346-1597, firstname.lastname@example.org or Charles Tappert, Ph.D., 914-773-3989, email@example.com
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