traffic classifier
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NSOM: A Real-Time Network-Based Intrusion Detection System Using Self-Organizing Maps
White Paper Different system parameters such as data collection, data preprocessing and classifier structure are discussed. The systems shows promise in its ability to classify regular v.s.irregular and possibly intrusive network traffic for a given host. [30 Jun 2008]
An Adaptive Anomaly Detector for Worm Detection
White Paper This paper presents an adaptive end-host anomaly detector where a supervised classifier trained as a traffic predictor is used to control a time-varying detection threshold. This comparison is robust to the choice of off-the-shelf classifier... [11 Apr 2008]
A Robust Classifier for Passive TCP/IP Fingerprinting
White Paper The authors analyze traffic captured from an Internet exchange point and compare this classifier to rule-based inference tools. Using probabilistic learning, a naive Bayesian classifier to passively infer a host's operating system from packet... [06 Nov 2007]
Passive Operating System Identification From TCP/IP Packet Headers
White Paper New classifiers were developed using machine-learning approaches including cross-validation testing, grouping OS names into fewer classes, and evaluating alternate classifier types. Accurate operating system (OS) identification by passive network... [06 Nov 2007]
Can We Contain Internet Worms?
White Paper Recent work has proposed a network centric approach to automate worm containment: network traffic is analyzed to derive a packet classifier that blocks (or rate-limits) worm propagation. Worm containment must be automatic because worms can spread... [09 Jun 2007]
Improving Web Spam Classification Using Rank-Time Features
White Paper In particular, the paper find that ensuring no overlapping domains between test and training sets is necessary to accurately test a web spam classifier. Second, the paper shows rank-time features can improve the performance of a web spam classifier. [09 Jun 2007]
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