JIRSÍK, Tomáš. Stream4Flow: Real-time IP Flow Host Monitoring using Apache Spark. Online. In NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium. Taipei, Taiwan: IEEE, 2018, p. 1-2. ISBN 978-1-5386-3416-5. Available from: https://dx.doi.org/10.1109/NOMS.2018.8406132.
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Basic information
Original name Stream4Flow: Real-time IP Flow Host Monitoring using Apache Spark
Authors JIRSÍK, Tomáš (203 Czech Republic, guarantor, belonging to the institution).
Edition Taipei, Taiwan, NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium, p. 1-2, 2 pp. 2018.
Publisher IEEE
Other information
Original language English
Type of outcome Proceedings paper
Confidentiality degree is not subject to a state or trade secret
Publication form electronic version available online
WWW URL
RIV identification code RIV/00216224:14610/18:00106894
Organization Ústav výpočetní techniky – Repository – Repository
ISBN 978-1-5386-3416-5
Doi http://dx.doi.org/10.1109/NOMS.2018.8406132
UT WoS 000541820800020
Keywords in English host monitoring; situation awareness; real-time; Stream4Flow
Links VI20162019014, research and development project.
Changed by Changed by: RNDr. Daniel Jakubík, učo 139797. Changed: 31/3/2023 04:06.
Abstract
In this paper, we present Stream4Flow, a framework for cyber situational awareness based on Apache Spark Streaming. We demonstrate utilization of Stream4Flow for real-time IP flow host monitoring in a large campus network. Contemporary IP flow analysis systems are not designed for the continuous host monitoring. Gaining the detailed overview of each host is not straightforward with these systems due to connection-based paradigm and performance challenges. We show that distributed stream processing is a natural solution for detailed IP flow host monitoring. Moreover, we describe a real-time host monitoring workflow in data streams in detail and present advantages of flow-based host monitoring in Apache Spark including real-time host profiling, dynamic level of detail and granularity.
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