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streamworks's Introduction

Streamworks

We provide an implementation of a dynamic graph library and algorithms for performing subgraph isomorphism on a graph stream.

Use

See the following paper for details on our streaming graph search algorithm and query optimization.

  • Choudhury S, L Holder, G Chin Jr, K Agarwal, and JT Feo. 2015. “A Selectivity-based Approach to Continuous Pattern Detection in Streaming Graphs.” In 18th International Conference on Extending Database Technology (EDBTT 2015). March 23-27, 2015, Brussels, Belgium.

Check out the following publications for graph query use cases for cyber security data.

  • Chin Jr G, S Choudhury, and K Agarwal. 2014. “StreamWorks—A System for Real-Time Graph Pattern Matching on Network Traffic.” Presented at FloCon 2015, January 12-15, 2015, Portland, Oregon.
  • Joslyn C, S Choudhury, D Haglin, B Howe, B Nickless, and B Olsen. 2013. “Massive Scale Cyber Traffic Analysis: A Driver for Graph Database Research.” In Proceedings of the First International Workshop on Graph Data Management Experience and Systems (GRADES 2013), Article No. 3. June 23, 2013, New York, New York. Association for Computing Machinery, New York. DOI: 10.1145/2484425.2484428.

Reproducing results from EDBT'15 paper

Using our Spark-Streaming module for network traffic aggregation

Contributors

  • Sutanay Choudhury, Pacific Northwest National Laboratory, USA
  • George Chin, Pacific Northwest National Laboratory, USA
  • Khushbu Agarwal, Pacific Northwest National Laboratory, USA
  • Sherman Beus, Pacific Northwest National Laboratory, USA
  • Vivek Datla, Pacific Northwest National Laboratory, USA
  • Patrick Mackey, Pacific Northwest National Laboratory, USA
  • Lawrence Holder, Washington State University, USA
  • Abhik Ray, Washington State University, USA

Publications

  1. Choudhury S, L Holder, G Chin Jr, K Agarwal, and JT Feo. 2015. “A Selectivity-based Approach to Continuous Pattern Detection in Streaming Graphs.” In 18th International Conference on Extending Database Technology (EDBTT 2015). March 23-27, 2015, Brussels, Belgium.
  2. Chin Jr G, S Choudhury, and K Agarwal. 2014. “StreamWorks—A System for Real-Time Graph Pattern Matching on Network Traffic.” Presented at FloCon 2015, January 12-15, 2015, Portland, Oregon.
  3. Morari, Alessandro, Vito Giovanni Castellana, Oreste Villa, Antonino Tumeo, Jesse Weaver, David Haglin, Sutanay Choudhury, and John Feo. "Scaling semantic graph databases in size and performance." IEEE Micro 4 (2014): 16-26.
  4. Chin Jr G, S Choudhury, JT Feo, and L Holder. 2014. “Predicting and Detecting Emerging Cyberattack Patterns Using StreamWorks.” In Proceedings of the 9th Annual Cyber and Information Security Research Conference (CISR’14), pp.93-96, April 8-10, 2014, Oak Ridge, Tennessee. Association for Computing Machinery, New York. DOI: 10.1145/2602087.2602111.
  5. Lieberman M, S Choudhury, M Hughes, D Patrone, S Hider, C Piatko, M Chapman, JP Marple, and D Silberberg. 2014. “Parasol: An Architecture for Cross-Cloud Federated Graph Querying.” In Proceedings of the DanaC: Workshop on Data Analytics in the Cloud, pp. 1-4. June 22, 2014, Snowbird, Utah. Association for Computing Machinery, New York. DOI: 10.1145/2627770.2627771.
  6. Joslyn C, S Choudhury, D Haglin, B Howe, B Nickless, and B Olsen. 2013. “Massive Scale Cyber Traffic Analysis: A Driver for Graph Database Research.” In Proceedings of the First International Workshop on Graph Data Management Experience and Systems (GRADES 2013), Article No. 3. June 23, 2013, New York, New York. Association for Computing Machinery, New York. DOI: 10.1145/2484425.2484428.
  7. Choudhury S, LB Holder, JT Feo, and G Chin Jr. “Fast Search for Multi-Relational Graphs.” In Proceedings of the Workshop on Dynamic Networks Management and Mining (DyNetMM '13), pp. 1-8. June 23, 2013, New York, New York. Association for Computing Machinery, New York. DOI: 10.1145/2489247.2489251.
  8. Choudhury S, LB Holder, G Chin Jr, A Ray, S Beus, and JT Feo. 2013. “StreamWorks—A System for Dynamic Graph Search.” In Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data (SIGMOD '13), pp. 1101-1104. June 22-27, 2013, New York, New York. Association for Computing Machinery, New York. DOI: 10.1145/2463676.2463697.

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