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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.
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Item Type: Report
Type of entry: Primary publication
Title: AuDI: Towards autonomous IoT device-type identification using periodic communications
Language: English
Date: 25 March 2019
Place of Publication: Darmstadt
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).

Status: Preprint
URN: urn:nbn:de:tuda-tuprints-85117
Additional Information:

Ersch. auch in: IEEE Journal on Selected Areas in Communications 2019; Special Issue on Artificial Intelligence and Machine Learning for Networking and Communications

Classification DDC: 000 Generalities, computers, information > 004 Computer science
Divisions: 20 Department of Computer Science > System Security Lab
Date Deposited: 25 Mar 2019 08:40
Last Modified: 16 Oct 2024 09:52
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/8511
PPN: 498643034
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