Hypersparse Traffic Matrices from Suricata Network Flows using GraphBLAS

Fuente: arXiv
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Autores principales: Houle, Michael, Jones, Michael, Wallmeyer, Dan, Brodeur, Risa, Burr, Justin, Jananthan, Hayden, Merrell, Sam, Michaleas, Peter, Perez, Anthony, Prout, Andrew, Kepner, Jeremy
Formato: Preprint
Publicado: 2024
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author Houle, Michael
Jones, Michael
Wallmeyer, Dan
Brodeur, Risa
Burr, Justin
Jananthan, Hayden
Merrell, Sam
Michaleas, Peter
Perez, Anthony
Prout, Andrew
Kepner, Jeremy
author_facet Houle, Michael
Jones, Michael
Wallmeyer, Dan
Brodeur, Risa
Burr, Justin
Jananthan, Hayden
Merrell, Sam
Michaleas, Peter
Perez, Anthony
Prout, Andrew
Kepner, Jeremy
contents Hypersparse traffic matrices constructed from network packet source and destination addresses is a powerful tool for gaining insights into network traffic. SuiteSparse: GraphBLAS, an open source package or building, manipulating, and analyzing large hypersparse matrices, is one approach to constructing these traffic matrices. Suricata is a widely used open source network intrusion detection software package. This work demonstrates how Suricata network flow records can be used to efficiently construct hypersparse matrices using GraphBLAS.
format Preprint
id arxiv_https___arxiv_org_abs_2409_12297
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Hypersparse Traffic Matrices from Suricata Network Flows using GraphBLAS
Houle, Michael
Jones, Michael
Wallmeyer, Dan
Brodeur, Risa
Burr, Justin
Jananthan, Hayden
Merrell, Sam
Michaleas, Peter
Perez, Anthony
Prout, Andrew
Kepner, Jeremy
Distributed, Parallel, and Cluster Computing
Hypersparse traffic matrices constructed from network packet source and destination addresses is a powerful tool for gaining insights into network traffic. SuiteSparse: GraphBLAS, an open source package or building, manipulating, and analyzing large hypersparse matrices, is one approach to constructing these traffic matrices. Suricata is a widely used open source network intrusion detection software package. This work demonstrates how Suricata network flow records can be used to efficiently construct hypersparse matrices using GraphBLAS.
title Hypersparse Traffic Matrices from Suricata Network Flows using GraphBLAS
topic Distributed, Parallel, and Cluster Computing
url https://arxiv.org/abs/2409.12297