On the physical robustness of RF on-chip nanostructured security

Kheir, Mohamed; Kreft, Heinz; Hölken, Iris; Knöchel, R.

doi:10.1016/j.jisa.2014.09.007

Cited by 5 publications

(4 citation statements)

References 18 publications

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“…Then, we generated the model signals by using (6) with the extracted m and ω 0 parameters. Finally, the model generated signals are also compared among them to calculate the sensitivity of analytical model (6). The signals' similarities (CS and CC max ) are calculated by using (1) for FD signals and using (2) for TD signals as discussed in Section II.…”

Section: A C-folded Uni-scatterer Tags (Classical Design)mentioning

confidence: 99%

“…From the windowed signals [ Fig. 9(b) and (c)], ω 0 and m are extracted to generate a model signal from the analytical model (6). Subsequently, a fitting comparison between the windowed FD signal and the model (6) generated signal is shown in Fig.…”

Section: B C-folded Quad-scatterers Tags (Optimized Design)mentioning

confidence: 99%

“…In the context of RF fingerprinting, several approaches to extract the fingerprints have been reported [4]- [7]. In these approaches the fingerprints are based on, for example, the minimum power responses of RFID tags [4], the wavelet fingerprinting [5], the nanostructured composite materials [6], and the phase information of back-scattered signals [7]. On the other hand, some studies on near-field physical-layer identification have also been reported in the literature [8]- [12].…”

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confidence: 99%

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Detection of Natural Randomness by Chipless RFID Approach and Its Application to Authentication

Ali

Perret

Barbot

et al. 2019

IEEE Trans. Microwave Theory Techn.

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In this paper, a chipless solution dedicated to the authentication of manufactured products is proposed. The proposed technique is an extension of chipless radio frequency identification (RFID) with a prevention of tags' cloning due to the use of natural randomness in the fabrication process. For the first time, we proposed a methodology to characterize the chipless RFID tags for the purpose of authentication. The proposed method has a high-level of security due to the employment of a database of authenticity. With a non-intrusive and non-destructive operation, the proposed method has promising possibilities for authentication applications, for example, the chipless tags can be inserted (or hidden) in the product packaging. The chipless tags are realized two times intermittently, where each realization is constituted of forty-five tags. These two different realizations share the same company, same technology, but different film mask to ensure the natural dimensional randomness. The similarity analysis is conducted inside each realization and also between two different realizations. With the help of this technique, it is possible to authenticate two chipless RFID tags exhibiting natural dimensional variations in their designs with a low probability of error.

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Section: A C-folded Uni-scatterer Tags (Classical Design)mentioning

confidence: 99%

Section: B C-folded Quad-scatterers Tags (Optimized Design)mentioning

confidence: 99%

mentioning

confidence: 99%

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Detection of Natural Randomness by Chipless RFID Approach and Its Application to Authentication

Ali

Perret

Barbot

et al. 2019

IEEE Trans. Microwave Theory Techn.

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“…Some protocols are proposed to improve its security level [6]. Physical attributes of back-scattered signals from the RFID tags can be used for authentication applications [7][8][9][10][11][12][13][14][15]. However, this functionality leads to additional blocks in the ASIC implementation, which increases the power consumption, reduces the reading distance, and significantly increases the final cost of the application.…”

Section: Introductionmentioning

confidence: 99%

A New Method of Secure Authentication Based on Electromagnetic Signatures of Chipless RFID Tags and Machine Learning Approaches

Nastasiu

Scripcaru

Digulescu

et al. 2020

Sensors

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In this study, we present the implementation of a neural network model capable of classifying radio frequency identification (RFID) tags based on their electromagnetic (EM) signature for authentication applications. One important application of the chipless RFID addresses the counterfeiting threat for manufacturers. The goal is to design and implement chipless RFID tags that possess a unique and unclonable fingerprint to authenticate objects. As EM characteristics are employed, these fingerprints cannot be easily spoofed. A set of 18 tags operating in V band (65–72 GHz) was designed and measured. V band is more sensitive to dimensional variations compared to other applications at lower frequencies, thus it is suitable to highlight the differences between the EM signatures. Machine learning (ML) approaches are used to characterize and classify the 18 EM responses in order to validate the authentication method. The proposed supervised method reached a maximum recognition rate of 100%, surpassing in terms of accuracy most of RFID fingerprinting related work. To determine the best network configuration, we used a random search algorithm. Further tuning was conducted by comparing the results of different learning algorithms in terms of accuracy and loss.

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2022

Chipless RFID Authentication

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On the physical robustness of RF on-chip nanostructured security

Cited by 5 publications

References 18 publications

Detection of Natural Randomness by Chipless RFID Approach and Its Application to Authentication

Detection of Natural Randomness by Chipless RFID Approach and Its Application to Authentication

A New Method of Secure Authentication Based on Electromagnetic Signatures of Chipless RFID Tags and Machine Learning Approaches

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