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can continuously collect a user’s intrinsic behavior reflected in keystroke dynamics, a customized signal processing scheme for feature extraction, and a support vector machine (SVM) algorithm based platform for user classification. The triboelectric keystroke device can transduce the typing motion including the effects of typing force and contact area into the electrical signals, and its touch-proof feature offers an improved signal-to-interference- plus-noise ratio (SINR) compared to previous active sensing devices based on triboelectrification.33, 35, 180 The SVM-based platform,181 with a rationally designed training stage and the capability of handling nonlinear features in keystrokes, is much more advanced than previously used statistical-based approach.180 This one-stop, hardware-plus- software security system is capable of authenticating and even precisely identifying users through their unique typing behaviors at the terminals, with an accuracy up to 98.7%. The promising application of this novel system in the financial and computing industry can push cyber security to a new level, where leaked passwords would possibly be of no concern. 4.2.1 Triboelectric Keystroke Device The proposed system consists of two processes, the training process and the authentication/identification process (Figure 41a). During the training process, users will input a string of characters through the keystroke device, followed by the acquisition of the induced electrical signals. Pre-defined features will then be extracted from the acquired signals and used to construct a profile database. During the authentication/identification process, a test profile will be built following the same procedures and cross-referenced with the existing profile database to either determine if the test subject is an authorized user (authentication) or identify who the test subject is (identification). The design of our 110PDF Image | HIGH PERFORMANCE TRIBOELECTRIC NANOGENERATOR AND ITS APPLICATIONS
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