Adaptive pattern recognition and neural networks
Adaptive pattern recognition and neural networks
Neural and concurrent real-time systems: the 6th generation
Neural and concurrent real-time systems: the 6th generation
Computer-Access Security Systems Using Keystroke Dynamics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural networks: algorithms, applications, and programming techniques
Neural networks: algorithms, applications, and programming techniques
Neural network based computer access security system for multiple users
Proceedings of the 23rd international conference on on Computers and industrial engineering
Discrete Time Processing of Speech Signals
Discrete Time Processing of Speech Signals
Linear Prediction of Speech
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A computer access security system, a reliable way of preventing unauthorized people for accessing, changing or deleting, and stealing the information, needed to be developed and implemented. In the present study, a neural network based system is proposed for computer access security for the issues of preventive security and detection of violation. Two types of data, time intervals between successive keystrokes during password entry through keyboard and voice patterns spoken via a microphone, are considered to deal with a situation of multiple users where each user has a certain password with different length. For each type of data, several multi-layered neural networks are designed and evaluated in terms of recognition accuracy. A committee neural network is formed consisting of six multi-layered neural networks. The committee decision was based on majority voting of the member networks. The committee neural network performance was better than the neural networks trained separately.