Dix-huit ans chez les sauvages : voyages et missions de Mgr Henry Faraud, áevãeque d'Anemour, vicaire apostolique de Mackensie dans l'extrãeme nord de l'Amerique britannique : d'apráes les documents de Mgr l'evãque d'Anemour / par Fernand-Michel.

http://www.archive.org/details/dixhuitanschezle00fararich

A view of the history, literature, and religion of the Hindoos : including a minute description of their manners and customs, and translations from their principal works / by Rev. W. Ward.

http://www.archive.org/details/wardshidoos00sethuoft

The Missionary pioneer, or, A brief memoir of the life, labours, and death of John Stewart, (man of colour) founder, under God of the mission among the Wyandotts at Upper Sandusky, Ohio / Published by Joseph Mitchell.

http://www.archive.org/details/missionarypionee00stewrich

Mining Anomalies Using Traffic Feature Distributions

The increasing practicality of large-scale flow capture makes it possible to conceive of traffic analysis methods that detect and identify a large and diverse set of anomalies. However the challenge of effectively analyzing this massive data source for anomaly diagnosis is as yet unmet. We argue that the distributions of packet features (IP addresses and ports) observed in flow traces reveals both the presence and the structure of a wide range of anomalies. Using entropy as a summarization tool, we show that the analysis of feature distributions leads to significant advances on two fronts: (1) it enables highly sensitive detection of a wide range of anomalies, augmenting detections by volume-based methods, and (2) it enables automatic classification of anomalies via unsupervised learning. We show that using feature distributions, anomalies naturally fall into distinct and meaningful clusters. These clusters can be used to automatically classify anomalies and to uncover new anomaly types. We validate our claims on data from two backbone networks (Abilene and Geant) and conclude that feature distributions show promise as a key element of a fairly general network anomaly diagnosis framework.