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Development of Committee Neural Network for Computer Access Security System

机译:计算机访问安全系统委员会神经网络的开发

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摘要

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.
机译:需要开发和实现一种计算机访问安全系统,它是一种防止未经授权的人员访问,更改或删除以及窃取信息的可靠方法。在本研究中,针对计算机访问安全性,针对预防性安全性和违规检测问题,提出了一种基于神经网络的系统。考虑了两种数据类型,即通过键盘输入密码时两次连续击键之间的时间间隔以及通过麦克风说出的语音模式,以应对多个用户的情况,其中每个用户都有一个长度不同的特定密码。对于每种类型的数据,设计了多个多层神经网络,并根据识别精度进行了评估。委员会神经网络由六个多层神经网络组成。委员会的决定基于成员网络的多数投票。委员会的神经网络性能优于单独训练的神经网络。

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