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An experimental study of security and privacy risks with emerging household appliances

Notra, Sukhvir, Siddiqi, Muhammad, Habibi Gharakheili, Hassan, Sivaraman, Vijay, Boreli, Roksana·2014·2014 IEEE Conference on Communications and Network Security

Abstract

Smart household appliances, ranging from light-bulbs and door-locks to power switches and smoke-alarms, are rapidly emerging in the marketplace, with predictions that over 2 billion devices will be installed within the next four years. However, security implementations vary widely across these devices, while privacy implications are unclear to users. In this paper we dissect the behavior of a few household devices, specifically the Phillips Hue light-bulb, the Belkin WeMo power switch, and the Nest smoke-alarm, and highlight the ease with which security and privacy can be compromised. We then propose a new solution to protect such devices by restricting access at the network-level. Our solution does not require changes from device manufacturers, reduces burden on the end-users, and allows security to be offered as an overlay service by the ISP or from a specialist provider in the cloud.

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Metadata

Authors
Notra, S., Siddiqi, M., Habibi Gharakheili, H., Sivaraman, V., & Boreli, R.
Venue
2014 IEEE Conference on Communications and Network Security
Publisher
IEEE
Published
2014-10
Pages
79-84
ISSN
2474-025X (ISSN-L)
OpenAlex
W2003797911
Cited by
189
References
0
FWCI
10.97
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: An experimental study of security and privacy risks with emerging household appliances. https://app.cochat.ai/papers/10.1109/cns.2014.6997469
The paper
Notra, S., Siddiqi, M., Habibi Gharakheili, H., Sivaraman, V., & Boreli, R. (2014). An experimental study of security and privacy risks with emerging household appliances. 2014 IEEE Conference on Communications and Network Security. https://doi.org/10.1109/cns.2014.6997469

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.