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BANKSAFE : A Visual Situational Awareness Tool for Large-Scale Computer Networks (Award for Outstanding Comprehensive Submission)

BANKSAFE : A Visual Situational Awareness Tool for Large-Scale Computer Networks (Award for Outstanding Comprehensive Submission)

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FISCHER, Fabian, Johannes FUCHS, Florian MANSMANN, Daniel KEIM, 2012. BANKSAFE : A Visual Situational Awareness Tool for Large-Scale Computer Networks (Award for Outstanding Comprehensive Submission). 2012 IEEE Conference on Visual Analytics Science and Technology (VAST). Seattle, WA, USA, 14. Okt 2012 - 19. Okt 2012. In: 2012 IEEE Conference on Visual Analytics Science and Technology (VAST). 2012 IEEE Conference on Visual Analytics Science and Technology (VAST). Seattle, WA, USA, 14. Okt 2012 - 19. Okt 2012. IEEE, pp. 257-258. ISBN 978-1-4673-4752-5. Available under: doi: 10.1109/VAST.2012.6400528

@inproceedings{Fischer2012-10BANKS-22517, title={BANKSAFE : A Visual Situational Awareness Tool for Large-Scale Computer Networks (Award for Outstanding Comprehensive Submission)}, year={2012}, doi={10.1109/VAST.2012.6400528}, isbn={978-1-4673-4752-5}, publisher={IEEE}, booktitle={2012 IEEE Conference on Visual Analytics Science and Technology (VAST)}, pages={257--258}, author={Fischer, Fabian and Fuchs, Johannes and Mansmann, Florian and Keim, Daniel} }

IEEE Conference on Visual Analytics Science & Technology 2012 : Seattle, Washington, USA 14 - 19 October 2012 ; Proceedings / Giuseppe Santucci and Matthew Ward (eds.). - Piscataway, NJ : IEEE, 2012. - S. 257-258. - ISBN 978-1-4673-4753-2 Mansmann, Florian BANKSAFE : A Visual Situational Awareness Tool for Large-Scale Computer Networks (Award for Outstanding Comprehensive Submission) eng Fischer, Fabian 2013-04-08T12:18:06Z 2012-10 Keim, Daniel deposit-license With the reliance of businesses, public institutions and individuals on large computer networks, maintaining their security becomes essential to ensure integrity. To achieve situational awareness, we developed Banksafe, which is a scalable, distributed and web-based visualization system to analyze health monitoring data and security datasets. To handle large amounts of data a cloud-based backend database is used to store and analyze the raw data. To evaluate the effectiveness of our approach we use both VAST 2012 mini challenges. Our case studies successfully identify suspicious events, trends and patterns using multiple visualizations. Fuchs, Johannes Fischer, Fabian 2013-04-08T12:18:06Z Keim, Daniel Fuchs, Johannes Mansmann, Florian

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