User Discrimination through Structured Writing on PDAs

This paper explores whether features of structured writing can serve to discriminate users of handheld devices such as Palm PDAs. Biometric authentication would obviate the need to remember a password or to keep it secret, requiring only that a user's manner of writing confirm his or her identity. Presumably, a user's dynamic and invisible writing style would be difficult for an imposter to imitate. We show how handwritten, multi-character strings can serve as personalized, non-secret passwords. A prototype system employing support vector machine classifiers was built to discriminate 52 users in a closed-world scenario. On high-quality data, strings as short as four letters achieved a false-match rate of 0.04%, at a corresponding false non-match rate of 0.64%. Strings of at least 8 to 16 letters in length delivered perfect results--a 0% equal-error rate. Very similar results were obtained upon decreasing the data quality or upon increasing the data quantity.