A PSD-based fingerprinting approach to detect IoT device spoofing
| Autor: | Romain Cayre, Vincent Nicomette, Mohamed Kaaniche, Florent Galtier, Guillaume Auriol |
|---|---|
| Přispěvatelé: | Équipe Tolérance aux fautes et Sûreté de Fonctionnement informatique (LAAS-TSF), Laboratoire d'analyse et d'architecture des systèmes (LAAS), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), APSYS (Blagnac), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Institut National des Sciences Appliquées (INSA) |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
021110 strategic
defence & security studies IoT Spoofing attack business.industry Computer science Fingerprint (computing) Real-time computing 0211 other engineering and technologies Context (language use) 02 engineering and technology [INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR] fingerprinting [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing Software deployment 020204 information systems Scalability 0202 electrical engineering electronic engineering information engineering Wireless Smart environment Smart environments business SDR PSD Building automation |
| Zdroj: | 25th IEEE Pacific Rim International Symposium on Dependable Computing (PRDC 2020) 25th IEEE Pacific Rim International Symposium on Dependable Computing (PRDC 2020), Dec 2020, Perth, Australia. ⟨10.1109/PRDC50213.2020.00015⟩ PRDC |
| DOI: | 10.1109/PRDC50213.2020.00015⟩ |
| Popis: | International audience; Spoofing attacks are generally difficult to detect and can have potentially harmful consequences on computer networks and applications. Wireless IoT networks, in the context of smart buildings or smart factories, are particularly vulnerable to these attacks. In this paper, we present a new physical device fingerprinting approach aiming at detecting spoofing attacks in wireless IoT environments. The proposed approach is based on the analysis of some properties of the physical signals emitted by connected devices, using their Power Spectral Density (PSD) to extract a frequency profile of their communications. This approach does not require any expensive equipment, is easy to deploy, and is resilient to non predictable phenomena in transmissions. The detection of spoofing attacks consists in comparing the fingerprint of a transmitting device with previously stored fingerprints of legitimate devices, by measuring the similarity of the corresponding PSDs and applying a community detection algorithm. The efficiency of this approach has been successfully tested using various experimental setups with connected devices supporting different wireless protocols (BLE, Zigbee). We also discuss the practical applicability of our approach, e.g. in an industrial environment by analysing its scalability and proposing solutions to tune and optimize its deployment at a large scale. |
| Databáze: | OpenAIRE |
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