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We present a novel security monitoring framework for intrusion detection in IaaS cloud infrastructures. The framework uses statistical anomaly detection techniques over data monitored both inside and outside each Virtual Machine instance. We present the architecture of our monitoring framework and describe the implementation of the real-time monitors and detectors. We also describe how the framework...
Detecting the intrusion usually depends on predicting the regular data traffics in wireless sensor networks. However, in fact, the data traffics are certainly affected by noise. In this paper, the theory of wavelet threshold is adopted to remove noise to increase the forecast accuracy of data traffics in WSN. Several numerical simulation verified that the forecasting precision is high, and achieved...
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