iotrim.github.io

IoTrim

Consumer IoT devices come with convenient services. However, since there are few strict privacy/security regulations and standards in the IoT context, device abuse is increasingly becoming a major privacy/security issue for consumers worldwide.

IoTrim, automatically monitors and blocks non-essential network activities, and identifies IoT devices’ information exposure and security threats, using privacy-preserving AI techniques to build insights and behavioral models from devices. IoTrim components run on the home router, and can be controlled through a smartphone app, a computer or the user’s voice (It offers easy-to-use, plug and play protection).

IoTrim prevents violations of individuals’ privacy by intercepting and blocking information exposure to third-party analytics and service providers, most of which are collecting personal data unbeknownst to the user and potentially breaking privacy regulations such as the GDPR and CCPA.

IoTrim List

This site contains a set of non-required destinations list from 31 consumer IoT devices and the software for producing the list. The list is created using a methodology for determining non-required destinations by automatically executing IoT device functions and determining the execution outcome while blocking selected destinations. IoT devices offer multiple types of functionality; however, for this list, we select only the main functions for every IoT device under test. However, from preliminary experiments we have seen that most devices use the same destinations for different functions.

The list contains 4 columns:

TEAM

IoTrim has been developed by researchers at Imperial College London and Northeastern University, and leverages advanced privacy preserving AI techniques for creating the trim lists. The protection techniques behind IoTrimmer have been reviewed by experts in top academic institutions, resulting in research papers published in top tier scientific conferences and EU/US funded research projects. Our team won important awards and our research has been featured in the Financial Times, New York Times, USA Today and the BBC.

NEWS

About this publication

– Title: Blocking Without Breaking: Identification and Mitigation of Non-Essential IoT Traffic

– Authors: Anna Maria Mandalari (Imperial College London), Daniel J. Dubois (Northeastern University), Roman Kolcun (Imperial College London), Muhammad Talha Paracha (Northeastern University), Hamed Haddadi (Imperial College London), and David Choffnes (Northeastern University)

– Download Full Text (PDF)

– Citation: @inproceedings{mandalari-pets21,

title={Blocking Without Breaking: Identification and Mitigation of Non-Essential IoT Traffic},

author={Mandalari, Anna Maria and Dubois, Daniel J.and Kolcun, Roman and Paracha, Muhammad Talha and Haddadi, Hamed and Choffnes, David},

booktitle={Proc. of the Privacy Enhancing Technologies Symposium (PETS)},

year={2021}

}