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Detecting IoT User Behavior and Sensitive Information in Encrypted IoT-App Traffic.

Alanoud Subahi1,2, George Theodorakopoulos3

  • 1School of Computer Science and Informatics, Cardiff University, Cardiff CF10 3AT, UK. subahiat@cardiff.ac.uk.

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Summary

A new IoT-app privacy inspector tool automatically detects sensitive data shared by smart home devices. This helps users protect their personal information and enhance Internet of Things (IoT) security.

Keywords:
IoTIoT privacy inspectorprivacysupervised machine learning

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Area of Science:

  • Computer Science
  • Cybersecurity
  • Network Security

Background:

  • Smart home devices, or Internet of Things (IoT) devices, are increasingly common in daily life.
  • These devices often rely on companion mobile applications for control and configuration.
  • IoT devices transmit user data from their apps directly to manufacturer clouds, raising privacy concerns.

Purpose of the Study:

  • To develop an automated tool, the IoT-app privacy inspector, for analyzing network traffic from IoT devices.
  • To identify specific network packets related to user interactions, sensitive Personal Identifiable Information (PII), and the content type of PII.
  • To empower IoT users with insights into their data sharing practices.

Main Methods:

  • Utilized a Random Forest classifier, a supervised machine learning algorithm, for feature extraction from network traffic.
  • Collected and labeled network traffic data from various IoT devices and their associated applications.
  • Trained and tested three distinct multi-class classifiers to categorize different types of network information.

Main Results:

  • Achieved high classification accuracy for identifying user interaction packets (99.4%).
  • Demonstrated exceptional accuracy in detecting packets carrying sensitive Personal Identifiable Information (PII) (99.8%).
  • Obtained a 99.8% accuracy rate for identifying the content type of sensitive information, such as user location.

Conclusions:

  • The developed IoT-app privacy inspector effectively automates the detection of sensitive data transmission from IoT devices.
  • The tool provides valuable information to users regarding their privacy in the context of smart home technology.
  • This research contributes to enhancing user privacy and security within the Internet of Things ecosystem.