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dc.contributor.authorZayuelas Muñoz, Jordi
dc.contributor.authorSuárez-Varela Maciá, José Rafael
dc.contributor.authorBarlet Ros, Pere
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Arquitectura de Computadors
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.date.accessioned2020-06-09T09:00:44Z
dc.date.available2020-06-09T09:00:44Z
dc.date.issued2019
dc.identifier.citationZayuelas, J.; Suárez-varela, J.; Barlet, P. Detecting cryptocurrency miners with NetFlow/IPFIX network measurements. A: IEEE International Workshop on Measurements and Networking. "M&N 2019 IEEE International Symposium on Measurements and Networking: Catania, Italy, July 8-10, 2019: proceedings". Institute of Electrical and Electronics Engineers (IEEE), 2019, p. 1-6.
dc.identifier.isbn978-1-7281-1273-2
dc.identifier.urihttp://hdl.handle.net/2117/190279
dc.description.abstractIn the last few years, cryptocurrency mining has become more and more important on the Internet activity and nowadays is even having a noticeable impact on the global economy. This has motivated the emergence of a new malicious activity called cryptojacking, which consists of compromising other machines connected to the Internet and leverage their resources to mine cryptocurrencies. In this context, it is of particular interest for network administrators to detect possible cryptocurrency miners using network resources without permission. Currently, it is possible to detect them using IP address lists from known mining pools, processing information from DNS traffic, or directly performing Deep Packet Inspection (DPI) over all the traffic. However, all these methods are still ineffective to detect miners using unknown mining servers or result too expensive to be deployed in real-world networks with large traffic volume. In this paper, we present a machine learning-based method able to detect cryptocurrency miners using NetFlow/IPFIX network measurements. Our method does not require to inspect the packets' payload; as a result, it achieves cost-efficient miner detection with similar accuracy than DPI-based techniques.
dc.description.sponsorshipThis work has been supported by the Spanish MINECO under contract TEC2017-90034-C2-1-R (ALLIANCE).
dc.format.extent6 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Informàtica::Seguretat informàtica
dc.subject.lcshComputer networks -- Security measures
dc.subject.lcshData mining
dc.subject.lcshTelecommunication -- Traffic
dc.subject.lcshCryptocurrencies
dc.subject.otherCryptojacking detection
dc.subject.otherCryptocurrency mining
dc.subject.otherMachine learning
dc.subject.otherNetFlow measurements
dc.titleDetecting cryptocurrency miners with NetFlow/IPFIX network measurements
dc.typeConference report
dc.subject.lemacOrdinadors, Xarxes d' -- Mesures de seguretat
dc.subject.lemacMineria de dades
dc.subject.lemacTelecomunicació -- Tràfic
dc.contributor.groupUniversitat Politècnica de Catalunya. CBA - Sistemes de Comunicacions i Arquitectures de Banda Ampla
dc.identifier.doi10.1109/IWMN.2019.8804995
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/8804995
dc.rights.accessOpen Access
local.identifier.drac28610039
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/AEI/TEC2017-90034-C2-1-R
local.citation.authorZayuelas, J.; Suárez-varela, J.; Barlet, P.
local.citation.contributorIEEE International Workshop on Measurements and Networking
local.citation.publicationNameM&N 2019 IEEE International Symposium on Measurements and Networking: Catania, Italy, July 8-10, 2019: proceedings
local.citation.startingPage1
local.citation.endingPage6


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