FCCE: Highly scalable distributed Feature Collection and Correlation Engine for low latency big data analytics

Douglas L. Schales, Xin Hu, Jiyong Jang, Reiner Sailer, Marc Ph Stoecklin, Ting Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

In this paper, we present the design, architecture, and implementation of a novel analysis engine, called Feature Collection and Correlation Engine (FCCE), that finds correlations across a diverse set of data types spanning over large time windows with very small latency and with minimal access to raw data. FCCE scales well to collecting, extracting, and querying features from geographically distributed large data sets. FCCE has been deployed in a large production network with over 450,000 workstations for 3 years, ingesting more than 2 billion events per day and providing low latency query responses for various analytics. We explore two security analytics use cases to demonstrate how we utilize the deployment of FCCE on large diverse data sets in the cyber security domain: 1) detecting fluxing domain names of potential botnet activity and identifying all the devices in the production network querying these names, and 2) detecting advanced persistent threat infection. Both evaluation results and our experience with real-world applications show that FCCE yields superior performance over existing approaches, and excels in the challenging cyber security domain by correlating multiple features and deriving security intelligence.

Original languageEnglish (US)
Title of host publication2015 IEEE 31st International Conference on Data Engineering, ICDE 2015
PublisherIEEE Computer Society
Pages1316-1327
Number of pages12
ISBN (Electronic)9781479979639
DOIs
StatePublished - May 26 2015
Event2015 31st IEEE International Conference on Data Engineering, ICDE 2015 - Seoul, Korea, Republic of
Duration: Apr 13 2015Apr 17 2015

Publication series

NameProceedings - International Conference on Data Engineering
Volume2015-May
ISSN (Print)1084-4627

Other

Other2015 31st IEEE International Conference on Data Engineering, ICDE 2015
CountryKorea, Republic of
CitySeoul
Period4/13/154/17/15

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Information Systems

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  • Cite this

    Schales, D. L., Hu, X., Jang, J., Sailer, R., Stoecklin, M. P., & Wang, T. (2015). FCCE: Highly scalable distributed Feature Collection and Correlation Engine for low latency big data analytics. In 2015 IEEE 31st International Conference on Data Engineering, ICDE 2015 (pp. 1316-1327). [7113379] (Proceedings - International Conference on Data Engineering; Vol. 2015-May). IEEE Computer Society. https://doi.org/10.1109/ICDE.2015.7113379