Interactive Web-Based Visual Analysis on Network Traffic Data
Network traffic data analysis is important for securing our computing environment and data. However, analyzing network traffic data requires tremendous effort because of the complexity of continuously changing network traffic patterns. To assist the user in better understanding and analyzing the net...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-12-01
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| Series: | Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2078-2489/14/1/16 |
| _version_ | 1797440934470746112 |
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| author | Dong Hyun Jeong Jin-Hee Cho Feng Chen Lance Kaplan Audun Jøsang Soo-Yeon Ji |
| author_facet | Dong Hyun Jeong Jin-Hee Cho Feng Chen Lance Kaplan Audun Jøsang Soo-Yeon Ji |
| author_sort | Dong Hyun Jeong |
| collection | DOAJ |
| description | Network traffic data analysis is important for securing our computing environment and data. However, analyzing network traffic data requires tremendous effort because of the complexity of continuously changing network traffic patterns. To assist the user in better understanding and analyzing the network traffic data, an interactive web-based visualization system is designed using multiple coordinated views, supporting a rich set of user interactions. For advancing the capability of analyzing network traffic data, feature extraction is considered along with uncertainty quantification to help the user make precise analyses. The system allows the user to perform a continuous visual analysis by requesting incrementally new subsets of data with updated visual representation. Case studies have been performed to determine the effectiveness of the system. The results from the case studies support that the system is well designed to understand network traffic data by identifying abnormal network traffic patterns. |
| first_indexed | 2024-03-09T12:16:34Z |
| format | Article |
| id | doaj.art-3073b640256e41c7ab21cc5f20be839c |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-03-09T12:16:34Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj.art-3073b640256e41c7ab21cc5f20be839c2023-11-30T22:46:06ZengMDPI AGInformation2078-24892022-12-011411610.3390/info14010016Interactive Web-Based Visual Analysis on Network Traffic DataDong Hyun Jeong0Jin-Hee Cho1Feng Chen2Lance Kaplan3Audun Jøsang4Soo-Yeon Ji5Department of Computer Science and Information Technology, University of the District of Columbia, Washington, DC 20759, USADepartment of Computer Science, Virginia Tech., Blacksburg, VA 22043, USADepartment of Computer Science, University of Texas at Dallas, Richardson, TX 75080, USADEVCOM Army Research Laboratory, Adelphi, MD 20783, USADepartment of Informatics, University of Oslo, 0373 Oslo, NorwayDepartment of Computer Science, Bowie State University, Bowie, MD 20715, USANetwork traffic data analysis is important for securing our computing environment and data. However, analyzing network traffic data requires tremendous effort because of the complexity of continuously changing network traffic patterns. To assist the user in better understanding and analyzing the network traffic data, an interactive web-based visualization system is designed using multiple coordinated views, supporting a rich set of user interactions. For advancing the capability of analyzing network traffic data, feature extraction is considered along with uncertainty quantification to help the user make precise analyses. The system allows the user to perform a continuous visual analysis by requesting incrementally new subsets of data with updated visual representation. Case studies have been performed to determine the effectiveness of the system. The results from the case studies support that the system is well designed to understand network traffic data by identifying abnormal network traffic patterns.https://www.mdpi.com/2078-2489/14/1/16web-based visual analysisuncertaintydiscrete wavelet transformation |
| spellingShingle | Dong Hyun Jeong Jin-Hee Cho Feng Chen Lance Kaplan Audun Jøsang Soo-Yeon Ji Interactive Web-Based Visual Analysis on Network Traffic Data Information web-based visual analysis uncertainty discrete wavelet transformation |
| title | Interactive Web-Based Visual Analysis on Network Traffic Data |
| title_full | Interactive Web-Based Visual Analysis on Network Traffic Data |
| title_fullStr | Interactive Web-Based Visual Analysis on Network Traffic Data |
| title_full_unstemmed | Interactive Web-Based Visual Analysis on Network Traffic Data |
| title_short | Interactive Web-Based Visual Analysis on Network Traffic Data |
| title_sort | interactive web based visual analysis on network traffic data |
| topic | web-based visual analysis uncertainty discrete wavelet transformation |
| url | https://www.mdpi.com/2078-2489/14/1/16 |
| work_keys_str_mv | AT donghyunjeong interactivewebbasedvisualanalysisonnetworktrafficdata AT jinheecho interactivewebbasedvisualanalysisonnetworktrafficdata AT fengchen interactivewebbasedvisualanalysisonnetworktrafficdata AT lancekaplan interactivewebbasedvisualanalysisonnetworktrafficdata AT audunjøsang interactivewebbasedvisualanalysisonnetworktrafficdata AT sooyeonji interactivewebbasedvisualanalysisonnetworktrafficdata |