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Title: Detecting consumer IoT devices through the lens of an ISP
Internet of Things (IoT) devices are becoming increasingly popular and offer a wide range of services and functionality to their users. However, there are significant privacy and security risks associated with these devices. IoT devices can infringe users' privacy by ex-filtrating their private information to third parties, often without their knowledge. In this work we investigate the possibility to identify IoT devices and their location in an Internet Service Provider's network. By analyzing data from a large Internet Service Provider (ISP), we show that it is possible to recognize specific IoT devices, their vendors, and sometimes even their specific model, and to infer their location in the network. This is possible even with sparsely sampled flow data that are often the only datasets readily available at an ISP. We evaluate our proposed methodology to infer IoT devices at subscriber lines of a large ISP. Given ground truth information on IoT devices location and models, we were able to detect more than 77% of the studied IoT devices from sampled flow data in the wild.  more » « less
Award ID(s):
1909020 1955227
PAR ID:
10287352
Author(s) / Creator(s):
; ; ; ; ; ;
Date Published:
Journal Name:
ANRW '21: Proceedings of the Applied Networking Research Workshop
Page Range / eLocation ID:
36 to 38
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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