Bringing PHY-Based Key Generation into the Field: An Evaluation for Practical Scenarios

Guillaume, René; Winzer, Fredrik; Czylwik, Andreas; Zenger, Christian; Paar, Christof

doi:10.1109/vtcfall.2015.7390857

Cited by 36 publications

(29 citation statements)

References 7 publications

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“…The variation over time of the RSS caused by motion and multipath fading can be quantized and used for generating secret keys. Most RSSbased key generation schemes are mainly applied in IEEE 802.11 [2], [10]- [12] and IEEE 802.15.4 systems [13], [14]. However, only one RSS value can be obtained from each packet/frame, which limits the key generation rate.…”

Section: Related Workmentioning

confidence: 99%

A Practical Secret Key Generation Scheme Based on Wireless Channel Characteristics for 5G Networks

Wang

Kang

et al. 2020

IEICE Trans. Inf. & Syst.

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Secret key generation based on channel characteristics is an effective physical-layer security method for 5G wireless networks. The issues of how to ensure the high key generation rate and correlation of the secret key under active attack are needed to be addressed. In this paper, a new practical secret key generation scheme with high rate and correlation is proposed. In our proposed scheme, Alice and Bob transmit independent random sequences instead of known training sequences or probing signals; neither Alice nor Bob can decode these random sequences or estimate the channel. User's random sequences together with the channel effects are used as common random source to generate the secret key. With this solution, legitimate users are able to share secret keys with sufficient length and high security under active attack. We evaluate the proposed scheme through both analytic and simulation studies. The results show that our proposed scheme achieves high key generation rate and key security, and is suitable for 5G wireless networks with resource-constrained devices.

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Section: Related Workmentioning

confidence: 99%

A Practical Secret Key Generation Scheme Based on Wireless Channel Characteristics for 5G Networks

Wang

Kang

et al. 2020

IEICE Trans. Inf. & Syst.

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“…While many works have focused on extracting secret keys (e.g. to be used for encryption and decryption of user data), such as [7], [8], [9], the focus of our work is to identify the original transmitter of data packets by exploiting the related PHY metadata.…”

Section: Related Workmentioning

confidence: 99%

Supervised Learning for Physical Layer Based Message Authentication in URLLC Scenarios

Weinand

Sattiraju

Karrenbauer

et al. 2019

2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall)

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PHYSEC based message authentication can, as an alternative to conventional security schemes, be applied within Ultra Reliable Low Latency Communication (URLLC) scenarios in order to meet the requirement of secure user data transmissions in the sense of authenticity and integrity. In this work, we investigate the performance of supervised learning classifiers for discriminating legitimate transmitters from illegimate ones in such scenarios. We further present our methodology of data collection using Software Defined Radio (SDR) platforms and the data processing pipeline including e.g. necessary preprocessing steps. Finally, the performance of the considered supervised learning schemes under different side conditions is presented.

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“…In [2] a good overview on this topic is given. While many works have focused on extracting secret keys between two communicating devices, such as [3], [4], [5], the focus of our work is on guaranteeing secure transmission with respect to authenticity of data packets from one device to another. One of the first works considering that idea has been for example [6], where an approach based on simulation of the wireless channel and hypothesis testing is presented for static scenarios and is later in [7] extended to time-variant scenarios.…”

Section: Related Workmentioning

confidence: 99%

Physical Layer Authentication for Mission Critical Machine Type Communication Using Gaussian Mixture Model Based Clustering

Weinand

Karrenbauer

Lianghai

et al. 2017

2017 IEEE 85th Vehicular Technology Conference (VTC Spring)

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Abstract-The application of Mission Critical Machine Type Communication (MC-MTC) in wireless systems is currently a hot research topic. Wireless systems are considered to provide numerous advantages over wired systems in e.g. industrial applications such as closed loop control. However, due to the broadcast nature of the wireless channel, such systems are prone to a wide range of cyber attacks. These range from passive eavesdropping attacks to active attacks like data manipulation or masquerade attacks. Therefore it is necessary to provide reliable and efficient security mechanisms. Some of the most important security issues in such a system are to ensure integrity as well as authenticity of exchanged messages over the air between communicating devices. In the present work, an approach on how to achieve this goal in MC-MTC systems based on Physical Layer Security (PHYSEC) is presented. A new method that clusters channel estimates of different transmitters based on a Gaussian Mixture Model is applied for that purpose. Further, an experimental proof-ofconcept evaluation is given and we compare the performance of our approach with a mean square error based detection method.

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Bringing PHY-Based Key Generation into the Field: An Evaluation for Practical Scenarios

Cited by 36 publications

References 7 publications

A Practical Secret Key Generation Scheme Based on Wireless Channel Characteristics for 5G Networks

A Practical Secret Key Generation Scheme Based on Wireless Channel Characteristics for 5G Networks

Supervised Learning for Physical Layer Based Message Authentication in URLLC Scenarios

Physical Layer Authentication for Mission Critical Machine Type Communication Using Gaussian Mixture Model Based Clustering

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