Identification of Wireless Devices From Their Physical Layer Radio-Frequency Fingerprints

2018 ◽  
pp. 6136-6146
Author(s):  
Gianmarco Baldini ◽  
Gary Steri ◽  
Raimondo Giuliani
Keyword(s):  
Radio Frequency ◽  
Research Work ◽  
Main Idea ◽  
Physical Layer ◽  
Manufacturing Processes ◽  
Wireless Devices ◽  
Electronic Circuits ◽  
Rf Components ◽  
Wireless Device ◽  
Rf Signal

Extensive research has been performed in recent years for the identification of wireless devices from their radio frequency (RF) emissions. The main idea of identifying a wireless device through its RF emissions is that the electronic circuits and the RF components have specific characteristics determined by the production and manufacturing processes. These characteristics, which result in unique differences, can be used to distinguish a wireless device from another because they appear as subtle modification of the RF signal in space even if the wireless device generates a signal conformant to the standard. This chapter describes the main techniques for the fingerprinting of wireless devices using their RF transmission. There are still however some key challenges to overcome. This chapter tries to identify them in this context as well as providing possible approaches to solve them. Further research work is needed to investigate the portability issues between fingerprints taken using different receivers, as well as to identify and remove potential other sources of bias.

Identification of Wireless Devices From Their Physical Layer Radio-Frequency Fingerprints

2019 ◽  
pp. 937-949
Author(s):  
Gianmarco Baldini ◽  
Gary Steri ◽  
Raimondo Giuliani
Keyword(s):  
Radio Frequency ◽  
Research Work ◽  
Main Idea ◽  
Physical Layer ◽  
Manufacturing Processes ◽  
Wireless Devices ◽  
Electronic Circuits ◽  
Rf Components ◽  
Wireless Device ◽  
Rf Signal

Extensive research has been performed in recent years for the identification of wireless devices from their radio frequency (RF) emissions. The main idea of identifying a wireless device through its RF emissions is that the electronic circuits and the RF components have specific characteristics determined by the production and manufacturing processes. These characteristics, which result in unique differences, can be used to distinguish a wireless device from another because they appear as subtle modification of the RF signal in space even if the wireless device generates a signal conformant to the standard. This chapter describes the main techniques for the fingerprinting of wireless devices using their RF transmission. There are still some key challenges to overcome. This chapter tries to identify them in this context as well as providing possible approaches to solve them. Further research work is needed to investigate the portability issues between fingerprints taken using different receivers, as well as to identify and remove potential other sources of bias.

scholarly journals Physical Layer Authentication and Identification of Wireless Devices Using the Synchrosqueezing Transform

2018 ◽  
Vol 8 (11) ◽  
pp. 2167 ◽  
Author(s):  
Gianmarco Baldini ◽  
Raimondo Giuliani ◽  
Gary Steri
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Physical Layer ◽  
The Novel ◽  
Wireless Devices ◽  
Time Frequency ◽  
Synchrosqueezing Transform ◽  
Communication Devices ◽  
Rf Devices ◽  
Wireless Device

This paper addresses the problem of authentication and identification of wireless devices using their physical properties derived from their Radio Frequency (RF) emissions. This technique is based on the concept that small differences in the physical implementation of wireless devices are significant enough and they are carried over to the RF emissions to distinguish wireless devices with high accuracy. The technique can be used both to authenticate the claimed identity of a wireless device or to identify one wireless device among others. In the literature, this technique has been implemented by feature extraction in the 1D time domain, 1D frequency domain or also in the 2D time frequency domain. This paper describes the novel application of the synchrosqueezing transform to the problem of physical layer authentication. The idea is to exploit the capability of the synchrosqueezing transform to enhance the identification and authentication accuracy of RF devices from their actual wireless emissions. An experimental dataset of 12 cellular communication devices is used to validate the approach and to perform a comparison of the different techniques. The results described in this paper show that the accuracy obtained using 2D Synchrosqueezing Transform (SST) is superior to conventional techniques from the literature based in the 1D time domain, 1D frequency domain or 2D time frequency domain.

scholarly journals A Database for the Radio Frequency Fingerprinting of Bluetooth Devices

Data ◽  
2020 ◽  
Vol 5 (2) ◽  
pp. 55
Author(s):  
Emre Uzundurukan ◽  
Yaser Dalveren ◽  
Ali Kara
Keyword(s):  
Wireless Networks ◽  
Radio Frequency ◽  
Data Acquisition ◽  
Data Acquisition System ◽  
Physical Layer ◽  
Acquisition System ◽  
Wireless Devices ◽  
Malicious Attacks ◽  
Distinctive Features ◽  
Important Requirement

Radio frequency fingerprinting (RFF) is a promising physical layer protection technique which can be used to defend wireless networks from malicious attacks. It is based on the use of the distinctive features of the physical waveforms (signals) transmitted from wireless devices in order to classify authorized users. The most important requirement to develop an RFF method is the existence of a precise, robust, and extensive database of the emitted signals. In this context, this paper introduces a database consisting of Bluetooth (BT) signals collected at different sampling rates from 27 different smartphones (six manufacturers with several models for each). Firstly, the data acquisition system to create the database is described in detail. Then, the two well-known methods based on transient BT signals are experimentally tested by using the provided data to check their solidity. The results show that the created database may be useful for many researchers working on the development of the RFF of BT devices.

Open Localization in Micro LeadFrame Package Using Space Domain Reflectometry

2013 ◽  
Author(s):  
J. Gaudestad ◽  
V. Talanov ◽  
A. Orozco ◽  
M. Marchetti
Keyword(s):  
Magnetic Field ◽  
Radio Frequency ◽  
Standing Wave ◽  
High Resistance ◽  
Space Domain ◽  
The Past ◽  
Open Defects ◽  
Rf Electronics ◽  
Rf Signal ◽  
The Magnetic Field

Abstract In the past couple years, Space Domain Reflectometry (SDR) has become a mainstream method to locate open defects among the major semiconductor manufacturers. SDR injects a radio frequency (RF) signal into the open trace creating a standing wave with a node at the open location. The magnetic field generated by the standing wave is imaged with a SQUID sensor using RF electronics. In this paper, we show that SDR can be used to non-destructively locate high resistance failures in Micro LeadFrame Packages (MLP).

scholarly journals A Physical Layer Security Enhancement Scheme under the Ambient Backscatter System

Symmetry ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 5
Author(s):  
Pengfei Hou ◽  
Jianping Gong ◽  
Jumin Zhao
Keyword(s):  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Physical Layer Security ◽  
Physical Layer ◽  
Artificial Noise ◽  
Identification System ◽  
Secrecy Rate ◽  
Channel Quality ◽  
Backscatter Communication ◽  
Ambient Backscatter

In this paper, we proposed a scheme that Injects artificial noise from the tag end (IANT) to enhance the physical layer security of the ambient backscatter communication (ABC) system. The difference between the ABC system and the traditional radio frequency identification system is whether it uses the radio frequency (RF) signals in the environment to supply energy and modulation information for passive tags. In the IANT scheme, we select the best tag to communicate with the reader according to the channel quality between tags and reader, and at the same time select another tag to generate artificial noise that affects the receiving effect of the eavesdropper. This paper uses the method of generating noise copies in the reader to reduce the interference of artificial noise on the signal received by the reader. The simulation results show that with the increase in channel quality between tags and reader and the increase in the number of tags, the proposed IANT scheme is significantly superior to the contrast scheme in terms of system achievable secrecy rate, effectively enhancing the physical layer security of the ABC system.

scholarly journals Reconfigurable Multiband Operation for Wireless Devices Embedding Antenna Boosters

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 808
Author(s):  
Jaume Anguera ◽  
Aurora Andújar ◽  
José Luis Leiva ◽  
Oriol Massó ◽  
Joakim Tonnesen ◽  
...  
Keyword(s):  
Ground Plane ◽  
Wireless Devices ◽  
Matching Network ◽  
Smart Meters ◽  
Efficient Operation ◽  
Frequency Bands ◽  
Tunable Capacitor ◽  
Prior Art ◽  
Wireless Device ◽  
Reconfigurable Matching Network

Wireless devices such as smart meters, trackers, and sensors need connections at multiple frequency bands with low power consumption, thus requiring multiband and efficient antenna systems. At the same time, antennas should be small to easily fit in the scarce space existing in wireless devices. Small, multiband, and efficient operation is addressed here with non-resonant antenna elements, featuring volumes less than 90 mm3 for operating at 698–960 MHz as well as some bands in a higher frequency range of 1710–2690 MHz. These antenna elements are called antenna boosters, since they excite currents on the ground plane of the wireless device and do not rely on shaping complex geometric shapes to obtain multiband behavior, but rather the design of a multiband matching network. This design approach results in a simpler, easier, and faster method than creating a new antenna for every device. Since multiband operation is achieved through a matching network, frequency bands can be configured and optimized with a reconfigurable matching network. Two kinds of reconfigurable multiband architectures with antenna boosters are presented. The first one includes a digitally tunable capacitor, and the second one includes radiofrequency switches. The results show that antenna boosters with reconfigurable architectures feature multiband behavior with very small sizes, compared with other prior-art techniques.

scholarly journals Electromagnetic radiation-based IC device identification and verification using deep learning

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Hong-xin Zhang ◽  
Jia Liu ◽  
Jun Xu ◽  
Fan Zhang ◽  
Xiao-tong Cui ◽  
...  
Keyword(s):  
Radio Frequency ◽  
Electromagnetic Radiation ◽  
Integrated Circuit ◽  
Information Leakage ◽  
Physical Layer ◽  
Descent Method ◽  
Gradient Descent Method ◽  
Absolute Level ◽  
Device Identification ◽  
Multifactor Authentication

Abstract The electromagnetic radiation of electronic equipment carries information and can cause information leakage, which poses a serious threat to the security system; especially the information leakage caused by encryption or other important equipment will have more serious consequences. In the past decade or so, the attack technology and means for the physical layer have developed rapidly. And system designers have no effective method for this situation to eliminate or defend against threats with an absolute level of security. In recent years, device identification has been developed and improved as a physical-level technology to improve the security of integrated circuit (IC)-based multifactor authentication systems. Device identification tasks (including device identification and verification) are accomplished by monitoring and exploiting the characteristics of the IC’s unintentional electromagnetic radiation, without requiring any modification and process to hardware devices, thereby providing versatility and adapting existing hardware devices. Device identification based on deep residual networks and radio frequency is a technology applicable to the physical layer, which can improve the security of integrated circuit (IC)-based multifactor authentication systems. Device identification tasks (identification and verification) are accomplished by passively monitoring and utilizing the inherent properties of IC unintended RF transmissions without requiring any modifications to the analysis equipment. After the device performs a series of operations, the device is classified and identified using a deep residual neural network. The gradient descent method is used to adjust the network parameters, the batch training method is used to speed up the parameter tuning speed, the parameter regularization is used to improve the generalization, and finally, the Softmax classifier is used for classification. In the end, 28 chips of 4 models can be accurately identified into 4 categories, then the individual chips in each category can be identified, and finally 28 chips can be accurately identified, and the verification accuracy reached 100%. Therefore, the identification of radio frequency equipment based on deep residual network is very suitable as a countermeasure for implementing the device cloning technology and is expected to be related to various security issues.

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