What is Normal? A Big Data Observational Science Model of Anonymized Internet Traffic
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.
Authors
- Albert Reuther (ORCID: https://orcid.org/0000-0002-3168-3663)
- Sandeep Pisharody (ORCID: https://orcid.org/0000-0003-3382-8579)
- Alex Pentland (ORCID: https://orcid.org/0000-0002-8053-9983)
- Ritesh Patel (ORCID: https://orcid.org/0000-0002-4441-3611)
- Michael E. Houle (ORCID: https://orcid.org/0000-0001-8486-8015)
- William Arcand
- Aydın Buluç (ORCID: https://orcid.org/0000-0001-7253-9038)
- Vijay Gadepally (ORCID: https://orcid.org/0000-0002-4598-2808)
- Timothy M. E. Davis (ORCID: https://orcid.org/0000-0003-0749-7411)
- Gabriel Wachman
- Lauren Milechin (ORCID: https://orcid.org/0000-0002-0554-3624)
- Julie Mullen
- William Bergeron
- Hayden Jananthan (ORCID: https://orcid.org/0000-0001-6877-0923)
- Jeremy Kepner (ORCID: https://orcid.org/0000-0001-9668-2613)
- David Bestor (ORCID: https://orcid.org/0009-0002-7684-1191)
- Piotr Łuszczek (ORCID: https://orcid.org/0000-0002-0089-6965)
- Matthew Hubbell
- Andrew M. Morris (ORCID: https://orcid.org/0000-0001-9173-9641)
- Andrew Prout (ORCID: https://orcid.org/0000-0002-5137-0672)
- Chansup Byun (ORCID: https://orcid.org/0009-0003-0183-914X)
- Guillermo Morales
- Daniel Burrill (ORCID: https://orcid.org/0000-0001-7417-4626)
- Michael G. Jones (ORCID: https://orcid.org/0000-0002-5434-4904)
- Antonio Rosa (ORCID: https://orcid.org/0000-0002-4595-1999)
- Charles Yee
- Daniel Grant
- Peter Michaleas
- Chasen Milner
Institutions
- Moscow Institute of Thermal Technology (RU)
Publication Details
- Published
- 2024-09-23
- DOI
- https://doi.org/10.1109/hpec62836.2024.10938480
- Citations
- 2
- Primary Topic
- Network Security and Intrusion Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.70