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Modeling and forecasting of network traffic data presents a number of challenges in recent paradigm due to the volatility of data. There are various methods used for forecasting time series including AR, MA, ARMA, ARIMA, Fourier transform, ANN, and fuzzy logic. Wavelets technique has attracted the attention of researchers and is a rapidly growing area of research. Using the wavelet transformation, a multiresolution representation of a traffic signal is possible which breaks the signal into its shifted and scaled versions. This breaking up of signal is used for smoothing of time series to...

In the age of information and communication technology, network models centralized or distributed systems are the good way to connect the user with a single platform.However,when such model and systems are implemented, different types of threat from system surrounding and from the boundary of a system are faced.Therefore we need to introduce new methods and techniques to avoid the threat faced by the systems.In this book we proposed new multi-tier techniques including soft computing, stochastic, hardware implementation and statistical approaches to avoid and minimize the attacks which affect...