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Improving Analytics Using Enriched Network Flow Data

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Manage episode 361742674 series 1264075
Content provided by Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Classic tool suites that are used to process network flow records deal with very limited detail on the network connections they summarize. These tools limit detail for several reasons: (1) to maintain long-baseline data, (2) to focus on security-indicative data fields, and (3) to support data collection across large or complex infrastructures. However, a consequence of this limited detail is that analysis results based on this data provide information about indications of behavior rather than information that accurately identifies behavior with high confidence. In this webcast, Tim Shimeall and Katherine Prevost discuss how to use IPFIX-formatted data with detail derived from deep packet inspection (DPI) to provide increased confidence in identifying behavior.

  continue reading

151 episodes

Artwork
iconShare
 
Manage episode 361742674 series 1264075
Content provided by Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Classic tool suites that are used to process network flow records deal with very limited detail on the network connections they summarize. These tools limit detail for several reasons: (1) to maintain long-baseline data, (2) to focus on security-indicative data fields, and (3) to support data collection across large or complex infrastructures. However, a consequence of this limited detail is that analysis results based on this data provide information about indications of behavior rather than information that accurately identifies behavior with high confidence. In this webcast, Tim Shimeall and Katherine Prevost discuss how to use IPFIX-formatted data with detail derived from deep packet inspection (DPI) to provide increased confidence in identifying behavior.

  continue reading

151 episodes

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