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Kalwar, AbhishekAssam Kaziranga University, India
(författare)
TVis : A Light-weight Traffic Visualization System for DDoS Detection
- Artikel/kapitelEngelska2019
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IEEE,2019
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LIBRIS-ID:oai:DiVA.org:umu-169723
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https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-169723URI
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https://doi.org/10.1109/iSAI-NLP48611.2019.9068666DOI
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Språk:engelska
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Sammanfattning på:engelska
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With rapid growth of network size and complexity, network defenders are facing more challenges in protecting networked computers and other devices from acute attacks. Traffic visualization is an essential element in an anomaly detection system for visual observations and detection of distributed DoS attacks. This paper presents an interactive visualization system called TVis, proposed to detect both low-rate and highrate DDoS attacks using Heron’s triangle-area mapping. TVis allows network defenders to identify and investigate anomalies in internal and external network traffic at both online and offline modes. We model the network traffic as an undirected graph and compute triangle-area map based on incidences at each vertex for each 5 seconds time window. The system triggers an alarm iff the system finds an area of the mapped triangle beyond the dynamic threshold. TVis performs well for both low-rate and high-rate DDoS detection in comparison to its competitors.
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Bhuyan, Monowar H.Umeå universitet,Institutionen för datavetenskap,Laboratory for Cyber Resilience, NAIST, Nara, Japan,Autonomous Distributed Systems Lab(Swepub:umu)mobh0003
(författare)
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Bhattacharyya, Dhruba K.Tezpur University, India
(författare)
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Kalita, Jugal K.University of Colorado at Colorado Springs
(författare)
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Kadobayashi, YoukiNara Institute of Science and Technology, Japan,Laboratory for Cyber Resilience
(författare)
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Elmroth, ErikUmeå universitet,Institutionen för datavetenskap,Autonomous Distributed Systems Lab(Swepub:umu)erel0001
(författare)
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Assam Kaziranga University, IndiaInstitutionen för datavetenskap
(creator_code:org_t)
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Ingår i:The Proceedings: IEEE9781728156316
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