Passive and Active Wireless Device Secure Identification

Secure wireless device identification is necessary if we want to ensure that any transmitted data reach only a desired receiver. However the fact that wireless communications are by nature broadcast creates unique challenges such as identity theft, eavesdropping for data interception, jamming attack...

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Bibliographic Details
Published in:IEEE access 2020, Vol.8, p.83312-83320
Main Authors: Delgado, Oscar, Kechtban, Louai, Lugan, Sebastien, Macq, Benoit
Format: Article
Language:English
Subjects:
80211
Authentication
Communication system security
covert channel
Eavesdropping
Electronic devices
emerging technologies
Hardware
Interception
Jamming
Machine learning
neural network
Object recognition
Physical unclonable function
PUF
Radioprint
Signal strength
Theft
Uniqueness
WiFi
Wireless communication
Wireless communications
wireless security
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Summary:Secure wireless device identification is necessary if we want to ensure that any transmitted data reach only a desired receiver. However the fact that wireless communications are by nature broadcast creates unique challenges such as identity theft, eavesdropping for data interception, jamming attacks to disrupt legitimate transmissions, etc. This paper proposes a new integrated radioprint framework (IRID) that has two main components. First, we propose a machine learning-based radio identification solution that relies on hardware variabilities of internal components of the transmitter caused during manufacturing, allowing us to achieve passive device identification. Second, we introduce a new kind of covert channel, based on variations in the emitted signal strength, which allows us to implement unique active device identification. We evaluate our proposed framework on an experimental test-bed of 20 identical WiFi devices. Although our experiments deal only with IEEE 802.11b, the approach can easily be extended to any wireless protocol. The experimental results show that our proposed solution can differentiate between network devices with accuracy in excess of 99% on the basis of a standard-compliant implementation.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.2991649