Network anomaly detection a machine learning perspective presents machine learning techniques in depth to help you more effectively detect and counter network intrusion discover the worlds research. Dhruba kumar bhattacharyya jugal kumar kalita network anomaly detection a machine learning perspective crc press boca raton london new york washington dc. Detection amachinelearning perspective dhrubakumarbhattacharyya jugalkumarkakta c crcpress 63 anomalydetection usingsupervised learning 193 network anomaly detection a machine learning perspective subject boca raton fla ua crc press 2014 . Parametric learning algorithms based on machine learning principles are therefore desirable as they can learn the nature of normal measurements and autonomously adapt to variations in the structure of normality a related work and contribution most methods of network anomaly detection are based on network traffic models. The book also provides material for hands on development so that you can code on a testbed to implement detection methods toward the development of your own intrusion detection system it offers a thorough introduction to the state of the art in network anomaly detection using machine learning approaches and systems
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