Khalifa University’s Emirates ICT Innovation Center (EBTIC)has scored first place in the “Suspicious Network Event Recognition” – a data mining challenge organized in association with the IEEE BigData 2019 conference, beating out 2,400 solutions that were submitted and winning US$1,000.
Dr. Dymitr Ruta, Chief Researcher, and Dr. Cen Ling, Senior Researcher, from EBTIC teamed up with the former EBTIC colleague Dr. Quang Hieu Vu on a challenge to decide which internet security alerts should be regarded as suspicious based on information extracted from network traffic logs.
The team developed an efficient model to extract essential summarized content from billions of traffic event data and used it to efficiently train eXtreme Gradient Boosting (XGBoost) – a state of the art machine learning model – to make the most accurate predictions. Their model outperformed the 249 competing teams from around the world, who submitted over 2,400 solutions.
The IEEE International Conference on Big Data (IEEE BigData) provides a leading forum for disseminating the latest research in Big Data. IEEE Big Data brings together leading researchers and developers from academia, research and the industry from all over the world to facilitate innovation, knowledge transfer and technical progress in addressing the 5 V’s (Velocity, Volume, Variety, Value and Veracity) of Big Data. The purpose of the conference is to identify deep technical and scientific nature of big data problems, and share the future direction on the development of next-generation solutions for data-driven decision making.
IEEE BigData 2019 is taking place in Los Angeles, California, USA from 9-12 December.
12 November 2019