document: Network intrusion and fault detection : a statistical anomaly approach With the advent and explosive growth of the global Internet and electronic commerce environments , adaptive/automatic network/service intrusion and anomaly detection in wide area data networks and e-commerce infrastructures is fast gaining critical research and practical importance . We present and demonstrate the use of a general-purpose hierarchical multitier multiwindow statistical anomaly detection technology and system that operates automatically , adaptively , and proactively , and can be applied to various networking technologies , including both wired and wireless ad hoc networks . Our method uses statistical models and multivariate classifiers to detect anomalous network conditions . Some numerical results are also presented that demonstrate that our proposed methodology can reliably detect attacks with traffic anomaly intensity as low as 3-5 percent of the typical background traffic intensity , thus promising to generate an effective early warning
doc_bio_tags: B I O B I O O O O O O O O O O O O O O B O O O O O O O O O O O O B I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I O O O O B I O B I O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O B I I O O O O O O O O O
extractive_keyphrases: network intrusion fault detection internet wide area data networks wireless ad hoc networks statistical models multivariate classifiers traffic anomaly intensity background traffic intensity
abstractive_keyphrases: computer network attacks denial of service early warning systems neural network classification ad hoc wireless experiments backpropagation perceptron-back propagation hybrid electronic commerce environment adaptive/automatic network/service intrusion e-commerce infrastructure hierarchical multitier statistical anomaly detection multiwindow anomaly detection wired ad hoc networks