Practical Cross-Layer Radio Frequency-Based Authentication Scheme for Internet of Things
Autor: | Zonghua Zhang, Yoram Haddad, Arie Haenel, Maryline Laurent |
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Rok vydání: | 2021 |
Předmět: |
sensors security
Computer science Network security TP1-1185 02 engineering and technology 01 natural sciences Biochemistry Article Field (computer science) Analytical Chemistry wireless sensor network network security 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering physical layer Instrumentation Authentication business.industry Chemical technology 010401 analytical chemistry Physical layer 020206 networking & telecommunications communication protocol internet of things Atomic and Molecular Physics and Optics 0104 chemical sciences Authentication protocol authentication Radio frequency business Communications protocol Wireless sensor network Computer network |
Zdroj: | Sensors, Vol 21, Iss 4034, p 4034 (2021) Sensors Volume 21 Issue 12 Sensors (Basel, Switzerland) |
ISSN: | 1424-8220 |
DOI: | 10.3390/s21124034 |
Popis: | The Internet of Things world is in need of practical solutions for its security. Existing security mechanisms for IoT are mostly not implemented due to complexity, budget, and energy-saving issues. This is especially true for IoT devices that are battery powered, and they should be cost effective to be deployed extensively in the field. In this work, we propose a new cross-layer approach combining existing authentication protocols and existing Physical Layer Radio Frequency Fingerprinting technologies to provide hybrid authentication mechanisms that are practically proved efficient in the field. Even though several Radio Frequency Fingerprinting methods have been proposed so far, as a support for multi-factor authentication or even on their own, practical solutions are still a challenge. The accuracy results achieved with even the best systems using expensive equipment are still not sufficient on real-life systems. Our approach proposes a hybrid protocol that can save energy and computation time on the IoT devices side, proportionally to the accuracy of the Radio Frequency Fingerprinting used, which has a measurable benefit while keeping an acceptable security level. We implemented a full system operating in real time and achieved an accuracy of 99.8% for the additional cost of energy, leading to a decrease of only ~20% in battery life. |
Databáze: | OpenAIRE |
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