Information Exposure From Consumer IoT Devices: A Multidimensional, Network-Informed Measurement Approach

By Jingjing Ren, Daniel J. Dubois, David R. Choffnes, A. Mandalari, Roman Kolcun, Hamed Haddadi. ACM/SIGCOMM Internet Measurement Conference, 2019

296 citations recorded by the source corpus.

Internet of Things (IoT) devices are increasingly found in everyday homes, providing useful functionality for devices such as TVs, smart speakers, and video doorbells. Along with their benefits come potential privacy risks, since these devices can communicate information about their users to other parties over the Internet. However, understanding these risks in depth and at scale is difficult due to heterogeneity in devices' user interfaces, protocols, and functionality. In this work, we conduct a multidimensional analysis of information exposure from 81 devices located in labs in the US and UK. Through a total of 34,586 rigorous automated and manual controlled experiments, we characterize information exposure in terms of destinations of Internet traffic, whether the contents of communication are protected by encryption, what are the IoT-device interactions that can be inferred from such content, and whether there are unexpected exposures of private and/or sensitive information (e.g., video surreptitiously transmitted by a recording device). We highlight regional differences between these results, potentially due to different privacy regulations in the US and UK. Last, we compare our controlled experiments with data gathered from an in situ user study comprising 36 participants.

Subfields: Information Systems, Sociology and Political Science, Signal Processing

View Paper: https://www.semanticscholar.org/paper/e92381f5b2010040a044a93a07216037d8bb8698

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems

1. Mauro Conti
2. Ahmad-Reza Sadeghi
3. Hidayet Aksu
4. Abbas Acar

In Sociology and Political Science

1. Mauro Conti
2. Hidayet Aksu
3. Abbas Acar

In Signal Processing

1. Mauro Conti
2. Ahmad-Reza Sadeghi
3. Hidayet Aksu
4. Abbas Acar

Citations in the corpus

• Peek-a-boo: i see your smart home activities, even encrypted! (2018, result): “Moreover, some other works [3– 5, 14, 24, 34, 47] worked on the device activity (event) inference problem, where the phrases device activity inference and user activity inference sometimes have been used interchangeably.”