What is Normal? A Big Data Observational Science Model of Anonymized Internet Traffic Article Swipe

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Jeremy Kepner , Hayden Jananthan , Michael G. Jones , William Arcand , David Bestor , William Bergeron , Daniel Burrill , Aydın Buluç , Chansup Byun , Timothy M. E. Davis , Vijay Gadepally , Daniel Grant , Michael E. Houle , Matthew Hubbell , Piotr Łuszczek , Lauren Milechin , Chasen Milner , Guillermo Morales , Andrew M. Morris , Julie Mullen , Ritesh Patel , Alex Pentland , Sandeep Pisharody , Andrew Prout , Albert Reuther , Antonio Rosa , Gabriel Wachman , Charles Yee , Peter Michaleas ·

YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2409.03111

Understanding what is normal is a key aspect of protecting a domain. Other domains invest heavily in observational science to develop models of normal behavior to better detect anomalies. Recent advances in high performance graph libraries, such as the GraphBLAS, coupled with supercomputers enables processing of the trillions of observations required. We leverage this approach to synthesize low-parameter observational models of anonymized Internet traffic with a high regard for privacy.

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Big data Observational study The Internet Data science Computer science World Wide Web Data mining Medicine Internal medicine

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Type: preprint
Language: en
Landing Page: https://doi.org/10.48550/arxiv.2409.03111
OA Status: green
Related Works: 10
OpenAlex ID: https://openalex.org/W4403555694

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DOI: https://doi.org/10.48550/arxiv.2409.03111

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Title: What is Normal? A Big Data Observational Science Model of Anonymized Internet Traffic

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Type: preprint

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Language: en

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Publication year: 2024

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Publication date: 2024-09-04

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Authors: Jeremy Kepner, Hayden Jananthan, Michael G. Jones, William Arcand, David Bestor, William Bergeron, Daniel Burrill, Aydın Buluç, Chansup Byun, Timothy M. E. Davis, Vijay Gadepally, Daniel Grant, Michael E. Houle, Matthew Hubbell, Piotr Łuszczek, Lauren Milechin, Chasen Milner, Guillermo Morales, Andrew M. Morris, Julie Mullen, Ritesh Patel, Alex Pentland, Sandeep Pisharody, Andrew Prout, Albert Reuther, Antonio Rosa, Gabriel Wachman, Charles Yee, Peter Michaleas

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Landing page: https://doi.org/10.48550/arxiv.2409.03111

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OA URL: https://doi.org/10.48550/arxiv.2409.03111

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Concepts: Big data, Observational study, The Internet, Data science, Computer science, World Wide Web, Data mining, Medicine, Internal medicine

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Cited by: 0

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