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Histogram-based traffic anomaly detection
We describe a new approach to feature-based anomaly detection that constructs histograms of different traffic features, models histogram patterns, and identifies deviations from the created models. Expand
Probabilistic lossy counting: an efficient algorithm for finding heavy hitters
We introduce Probabilistic lossy counting (PLC), which enhances lossy count in computing network traffic heavy hitters. Expand
IBM PowerNP network processor: Hardware, software, and applications
This paper provides an overview of the IBM PowerNPTM NP4GS3 network processor and how it addresses these issues. Expand
On the 95-Percentile Billing Method
The 95-percentile method is used widely for billing ISPs and websites. Expand
The eternal sunshine of the sketch data structure
We introduce two techniques to address this problem based on the observation that real-world data streams often have many transient keys that appear for short time periods and do not re-appear later on. Expand
INCA: An Agent-Based Network Control Architecture
This paper describes the design and implementation of INCA, an open architecture for the distributed management of multi-service networks and systems applications. Expand
A Two-Layered Anomaly Detection Technique Based on Multi-modal Flow Behavior Models
We present a novel technique to detect traffic anomalies based on network flow behavior in different traffic features. Expand
PowerNP Network Processor: Hardware, Software And Applications
Deep packet processing is migrating to the edges of service provider networks to simplify and speed up core functions. On the other hand, the cores of such networks are migrating to the switching ofExpand
Bandwidth allocation for non-responsive flows with active queue management
This paper addresses the problem of configuring active queue management systems (e.g. WRED and RIO) for service level specifications in internetworks. In particular, we focus on assured forwardingExpand
A practical approach to type inference for EuLisp
This paper describes a practical approach to type inference realized in a module and application compiler forEuLisp. Expand