@inproceedings{a2dca15ad3344166ac4c38bf047c96ae,
title = "Visual Analytics for Real-Time Flight Behavior Threat Assessment",
abstract = "We propose integrating data visualization and machine learning techniques to support Air Traffic Controller (ATC) systems for detecting and identifying friendly/unfriendly aircraft. Our platform composes data-driven decisions to optimize strategic, and operative elements of an ATC system and mitigates its drawbacks by analyzing real-time data from a radar system. A threat assessment approach that incorporates flight behavior assessment, based on visualizing flight data together with flight anomaly prediction and flight origin/destination prediction can be used in cases where the system fails. Furthermore, our proposed integrated tool lets users quickly identify flights and security concerns by analyzing and visualizing data.",
author = "Sun, {Bo Beth} and Eric Zielonka and Aleksandr Fritz and Matthew Schofield and Brennan Ringel and Brendan Armstrong and Ho, {Shen Shyang} and Anthony Breitzman and Jason Snouffer and Jean Kirschner and Kimberly Davis",
note = "Funding Information: ACKNOWLEDGMENT We would like to thank ASRC Federal for funding support of this work. Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Big Data, Big Data 2018 ; Conference date: 10-12-2018 Through 13-12-2018",
year = "2019",
month = jan,
day = "22",
doi = "10.1109/BigData.2018.8622086",
language = "English (US)",
series = "Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3607--3612",
editor = "Yang Song and Bing Liu and Kisung Lee and Naoki Abe and Calton Pu and Mu Qiao and Nesreen Ahmed and Donald Kossmann and Jeffrey Saltz and Jiliang Tang and Jingrui He and Huan Liu and Xiaohua Hu",
booktitle = "Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018",
address = "United States",
}