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AuDI: Towards autonomous IoT device-type identification using periodic communications

Marchal, Samuel ; Miettinen, Markus ; Nguyen, Thien Duc ; Sadeghi, Ahmad-Reza ; Asokan, N. (2019)
AuDI: Towards autonomous IoT device-type identification using periodic communications.
In: IEEE Journal on Selected Areas in Communications
Artikel, Erstveröffentlichung

Kurzbeschreibung (Abstract)

IoT devices are being widely deployed. But the huge variance among them in the level of security and requirements for network resources makes it unfeasible to manage IoT networks using a common generic policy. One solution to this challenge is to define policies for classes of devices based on device type. In this paper, we present AUDI, a system for quickly and effectively identifying the type of a device in an IoT network by analyzing their network communications. AUDI models the periodic communication traffic of IoT devices using an unsupervised learning method to perform identification. In contrast to prior work, AUDI operates autonomously after initial setup, learning, without human intervention nor labeled data, to identify previously unseen device types. AUDI can identify the type of a device in any mode of operation or stage of lifecycle of the device. Via systematic experiments using 33 off-the-shelf IoT devices, we show that AUDI is effective (98.2% accuracy).

Typ des Eintrags: Artikel
Erschienen: 2019
Autor(en): Marchal, Samuel ; Miettinen, Markus ; Nguyen, Thien Duc ; Sadeghi, Ahmad-Reza ; Asokan, N.
Art des Eintrags: Erstveröffentlichung
Titel: AuDI: Towards autonomous IoT device-type identification using periodic communications
Sprache: Englisch
Publikationsjahr: Juni 2019
Verlag: IEEE
Titel der Zeitschrift, Zeitung oder Schriftenreihe: IEEE Journal on Selected Areas in Communications
URL / URN: https://tuprints.ulb.tu-darmstadt.de/8511
Kurzbeschreibung (Abstract):

IoT devices are being widely deployed. But the huge variance among them in the level of security and requirements for network resources makes it unfeasible to manage IoT networks using a common generic policy. One solution to this challenge is to define policies for classes of devices based on device type. In this paper, we present AUDI, a system for quickly and effectively identifying the type of a device in an IoT network by analyzing their network communications. AUDI models the periodic communication traffic of IoT devices using an unsupervised learning method to perform identification. In contrast to prior work, AUDI operates autonomously after initial setup, learning, without human intervention nor labeled data, to identify previously unseen device types. AUDI can identify the type of a device in any mode of operation or stage of lifecycle of the device. Via systematic experiments using 33 off-the-shelf IoT devices, we show that AUDI is effective (98.2% accuracy).

URN: urn:nbn:de:tuda-tuprints-85117
Zusätzliche Informationen:

Special Issue on Artificial Intelligence and Machine Learning for Networking and Communications

Sachgruppe der Dewey Dezimalklassifikatin (DDC): 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Systemsicherheit
Hinterlegungsdatum: 31 Mär 2019 19:55
Letzte Änderung: 31 Mär 2019 19:55
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