The Day-After-Tomorrow: On the Performance of Radio Fingerprinting over Time

Author:

Saeif Alhazbi1ORCID,Savio Sciancalepore2ORCID,Gabriele Oligeri1ORCID

Affiliation:

1. Hamad Bin Khalifa University, Qatar

2. Technische Universiteit Eindhoven (TU/e), Netherlands

Funder

Qatar National Research Fund

Nederlandse Organisatie voor Wetenschappelijk Onderzoek

Publisher

ACM

Reference39 articles.

1. Improving security of the Internet of Things via RF fingerprinting based device identification system

2. Amani Al-Shawabka , Philip Pietraski , Sudhir  B Pattar , Francesco Restuccia , and Tommaso Melodia . 2021 . DeepLoRa: Fingerprinting LoRa devices at scale through deep learning and data augmentation . In Proceedings of the Twenty-second International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing. 251–260 . Amani Al-Shawabka, Philip Pietraski, Sudhir B Pattar, Francesco Restuccia, and Tommaso Melodia. 2021. DeepLoRa: Fingerprinting LoRa devices at scale through deep learning and data augmentation. In Proceedings of the Twenty-second International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing. 251–260.

3. Exposing the Fingerprint: Dissecting the Impact of the Wireless Channel on Radio Fingerprinting

4. Assessment of Features and Classifiers for Bluetooth RF Fingerprinting

5. Feature Selection for RF Fingerprinting With Multiple Discriminant Analysis and Using ZigBee Device Emissions

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