A Neural Network Application for a Computer Access Security System: Keystroke Dynamics versus Voice Patterns

A neural network architecture is proposed to deal with a situation of multiple users where each user has his/her own password with different length. Two groups of experiments were conducted to find a better and a reliable way for a computer access security system. The neural networks are trained using time intervals between successive keystrokes during password entry through keyboard and voice patterns spoken via a microphone, respectively. The performance of the neural networks designed for each of the experiments is evaluated in terms of recognition accuracy. Two major issues, preventive security and detection of violations, which may be in question for a security system, are examined.