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CYBER ANOMALY DETECTION USING AN ARTIFICIAL NEURAL NETWORK
CYBER ANOMALY DETECTION USING AN ARTIFICIAL NEURAL NETWORK
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机译：基于人工神经网络的网络异常检测
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摘要
A hardware-based artificial neural network receives data patterns from a source. The hardware-based artificial neural network is trained using the data patterns such that it learns normal data patterns. A new data pattern is identified when the data pattern deviates from the normal data patterns. The hardware-based artificial neural network is then trained using the new data pattern such that the hardware-based artificial neural network learns the new data pattern by altering one or more synaptic weights associated with the new data pattern. The rate at which the hardware-based artificial neural network alters the one or more synaptic weights is monitored, wherein a training rate that is greater than a threshold indicates that the new data pattern is malicious.
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