Home > Published Issues > 2023 > Volume 18, No. 5, May 2023 >
JCM 2023 Vol.18(5): 283-293
Doi: 10.12720/jcm.18.5.283-293

Automating Internet of Things Network Traffic Collection with Robotic Arm Interactions

Xi Jiang1,* and Noah Apthorpe2
1.Department of Computer Science, University of Chicago, Chicago, IL, 60637, USA
2.Department of Computer Science, Colgate University, Hamilton, NY, 13346, US

Manuscript received September 15, 2022; revised October 30, 2022; accepted December 23, 2022.

Abstract—Consumer Internet of things research often involves collecting network traffic sent or received by IoT devices. These data are typically collected via crowdsourcing or while researchers manually interact with IoT devices in a laboratory setting. However, manual interactions and crowdsourcing are often tedious, expensive, inaccurate, or do not provide comprehensive coverage of possible IoT device behaviors. We present a new method for generating IoT network traffic using a robotic arm to automate user interactions with devices. This eliminates manual button pressing and enables permutation-based interaction sequences that rigorously explore the range of possible device behaviors. We test this approach with an Arduinocontrolled robotic arm, a smart speaker, and a smart thermostat, using machine learning to demonstrate that collected network traffic contains information about device interactions that could be useful for network, security, or privacy analyses. We also provide source code and documentation allowing researchers to easily automate IoT device interactions and network traffic collection in future studies.

Keywords—test-bed and trials, cyber-physical systems, other communications and networking topics.

Cite: Xi Jiang and Noah Apthorpe, "Automating Internet of Things Network Traffic Collection with Robotic Arm Interactions," Journal of Communications vol. 18, no. 5, pp. 283-293, May 2023. Doi: 10.12720/jcm.18.5.283-293

Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.