• DocumentCode
    249339
  • Title

    SiLK: A Tool Suite for Unsampled Network Flow Analysis at Scale

  • Author

    Thomas, Martyn ; Metcalf, Leigh ; Spring, J. ; Krystosek, Paul ; Prevost, Katherine

  • Author_Institution
    Software Eng. Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
  • fYear
    2014
  • fDate
    June 27 2014-July 2 2014
  • Firstpage
    184
  • Lastpage
    191
  • Abstract
    A large organization can generate over ten billion network flow records per day, a high-velocity data source. Finding useful, security-related anomalies in this volume of data is challenging. Most large network flow tools sample the data to make the problem manageable, but sampling unacceptably reduces the fidelity of analytic conclusions. In this paper we discuss SiLK, a tool suite created to analyze this high-volume data source without sampling. SiLK implementation and architectural design are optimized to manage this Big Data problem. SiLK provides not just network flow capture and analysis, but also includes tools to analyze large sets and dictionaries that frequently relate to network flow data, incorporating higher-variety data sources. These tools integrate disparate data sources with SiLK analysis.
  • Keywords
    Big Data; Internet; dictionaries; Big Data problem; SiLK; System for Internet-Level Knowledge; architectural design; dictionaries; high-velocity data source; high-volume data source; security-related anomalies; tool suite; unsampled network flow analysis; IP networks; Indexes; Open source software; Ports (Computers); Protocols; Routing; Security; Network Flow; Network Security; Network traffic analysis; Open-source tools; Security;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data (BigData Congress), 2014 IEEE International Congress on
  • Conference_Location
    Anchorage, AK
  • Print_ISBN
    978-1-4799-5056-0
  • Type

    conf

  • DOI
    10.1109/BigData.Congress.2014.34
  • Filename
    6906777