research-article

Attacks on physical-layer identification

Authors:

Heinrich Luecken,

Karim El DefrawyAuthors Info & Claims

WiSec '10: Proceedings of the third ACM conference on Wireless network security

Pages 89 - 98

https://doi.org/10.1145/1741866.1741882

Published: 22 March 2010 Publication History

Abstract

Physical-layer identification of wireless devices, commonly referred to as Radio Frequency (RF) fingerprinting, is the process of identifying a device based on transmission imperfections exhibited by its radio transceiver. It can be used to improve access control in wireless networks, revent device cloning and complement message authentication protocols. This paper studies the feasibility of performing impersonation attacks on the modulation-based and transient-based fingerprinting techniques. Both techniques are vulnerable to impersonation attacks; however, transient-based techniques are more difficult to reproduce due to the effects of the wireless channel and antenna in their recording process. We assess the feasibility of performing impersonation attacks by extensive measurements as well as simulations using collected data from wireless devices. We discuss the implications of our findings and how they affect current device identification techniques and related applications.

References

[1]

Fingeprint verification competitions (FVC). http://bias.csr.uni-bo.it/fvc2006/.

[2]

Agilent. Digital Signal Analyzer (DSA) 90804A, 2008. http://www.home.agilent.com/.

[3]

Bishop, C. Pattern Recognition and Machine Learning. Springer, 2006.

Digital Library

[4]

Blossom, E. GNU software radio. http://www.gnu.org/software/gnuradio/.

[5]

Bolle, R., Connell, J., Pankanti, S., Ratha, N., and Senior, A. Guide to Biometrics. Springer, 2003.

Digital Library

[6]

Brik, V., Banerjee, S., Gruteser, M., and Oh, S. Wireless device identification with radiometric signatures. In Proc. ACM International Conference on Mobile Computing and Networking (MobiCom) (2008).

Digital Library

[7]

Danev, B., Heydt-Benjamin, T.S., and Čapkun, S. Physical-layer identification of RFID devices. In Proc. USENIX Security Symposium (2009).

Digital Library

[8]

Danev, B., and Čapkun, S. Transient-based identification of wireless sensor nodes. In Proc. ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN) (2009).

Digital Library

[9]

Edman, M., and Yener, B. Active attacks against modulation-based radiometric identification. TR 09-02, Rensselaer Institute of Technology, Aug. 2009.

[10]

Ellis, K., and Serinken, N. Characteristics of radio transmitter fingerprints. Radio Science 36 (2001), 585--597.

[11]

Ettus, M. Universal software radio peripheral (USRP). http://www.ettus.com/.

[12]

Faria, D.B., and Cheriton, D.R. Detecting identity-based attacks in wireless networks using signalprints. In Proc. ACM Workshop on Wireless Security (WiSe) (2006).

Digital Library

[13]

Hall, J., Barbeau, M., and Kranakis, E. Enhancing intrusion detection in wireless networks using radio frequency fingerprinting. In Proc. Communications, Internet, and Information Technology (CIIT) (2004).

[14]

Hall, J., Barbeau, M., and Kranakis, E. Radio frequency fingerprinting for intrusion detection in wireless networks. Manuscript, 2005. http://wiki.uni.lu/secan-lab/Hall2005.html.

[15]

Hall, J., Barbeau, M., and Kranakis, E. Detecting rogue devices in Bluetooth networks using radio frequency fingerprinting. In Proc. IASTED International Conference on Communications and Computer Networks (CCN) (2006).

[16]

Hippenstiel, R., and Payal, Y. Wavelet based transmitter identification. In Proc. International Symposium on Signal Processing and Its Applications (ISSPA) (1996).

[17]

IEEE Standards Association. IEEE Standard 802.11b-1999: Wireless LAN MAC and PHY Specifications, 1999.

[18]

Kaplan, D., and Stanhope, D. Waveform collection for use in wireless telephone identification. US Patent 5999806, 1999.

[19]

Oppenheim, A., Schafer, R., and Buck, J. Discrete-Time Signal Processing. Prentice-Hall Signal Processing Series, 1998.

Digital Library

[20]

O.Ureten, and N.Serinken. Wireless security through RF fingerprinting. Canadian Journal of Electrical and Computer Engineering 32, 1 (Winter 2007).

[21]

Patwari, N., and Kasera, S. Robust location distinction using temporal link signatures. In Proc. ACM International Conference on Mobile Computing and Networking (MobiCom) (2007).

Digital Library

[22]

Rassmussen, K., and Capkun, S. Implications of radio fingerprinting on the security of sensor networks. In Proc. International ICST Conference on Security and Privacy in Communication Networks (SecureComm) (2007).

[23]

Schmidl, T., and Cox, D. Robust frequency and timing synchronization for ofdm. IEEE Transactions on Communications 45, 12 (1997).

[24]

Tekbas, O., Ureten, O., and Serinken, N. Improvement of transmitter identification system for low SNR transients. In Elec. Letters (2004), vol. 40.

[25]

Tektronix. Arbitrary Waveform Generator 7000. http://www.tek.com/products/signal_sources/awg7000/.

[26]

Toonstra, J., and Kinsner, W. Transient analysis and genetic algorithms for classification. In Proc. IEEE Conference on Communications, Power, and Computing (WESCANEX) (1995).

[27]

Toonstra, J., and Kinsner, W. A radio transmitter fingerprinting system ODO-1. In Proc. Canadian Conference on Electrical and Computer Engineering (1996).

[28]

Wang, B., Omatu, S., and Abe, T. Identification of the defective transmission devices using the wavelet transform. IEEE Transactions on Pattern Analysis and Machine Intelligence 27, 6 (2005), 696--710.

Digital Library

[29]

Xiao, L., Greenstein, L., Mandayam, N., and Trappe, W. Fingerprints in the ether: Using the physical layer for wireless authentication. In Proc. IEEE International Conference on Communications (ICC) (2007).

Cited By

Zhou QHe YYang KChi T(2024)Physical-Layer Identification of Wireless IoT Nodes Through PUF-Controlled Transmitter Spectral RegrowthIEEE Transactions on Microwave Theory and Techniques10.1109/TMTT.2023.330505572:2(1045-1055)Online publication date: Feb-2024
https://doi.org/10.1109/TMTT.2023.3305055
Wu CZeng Q(2024)Turning Noises to Fingerprint-Free “Credentials”: Secure and Usable Drone AuthenticationIEEE Transactions on Mobile Computing10.1109/TMC.2024.337350323:10(10161-10174)Online publication date: Oct-2024
https://doi.org/10.1109/TMC.2024.3373503
Pan QAn ZZhao XYang L(2024)The Power of Precision: High-Resolution Backscatter Frequency Drift in RFID IdentificationIEEE Transactions on Mobile Computing10.1109/TMC.2023.334768123:8(8370-8385)Online publication date: Aug-2024
https://doi.org/10.1109/TMC.2023.3347681
Show More Cited By

Index Terms

Attacks on physical-layer identification

Recommendations

Physical-Layer Attacks and Their Impact on Wireless Networks: Two Case Studies
WiSec '22: Proceedings of the 15th ACM Conference on Security and Privacy in Wireless and Mobile Networks

In this talk, I will discuss physical layer attacks on wireless networks, including attacks on GNSS systems, UWB ranging and cellular networks. Although these attacks differ in their goals and adversarial models, they share some commonalities - they ...
The Feasibility of Launching Reduction of Quality (RoQ) Attacks in 802.11 Wireless Networks
ICPADS '08: Proceedings of the 2008 14th IEEE International Conference on Parallel and Distributed Systems

In this paper, we discuss wireless Reduction of Quality (RoQ) attacks against the transmission control protocol (TCP). RoQ attacks can dramatically degrade the TCP performance with a less number of wireless jamming attacking packets, which makes them ...
A Real-Time Implementation of the Mobile WiMAX ARQ and Physical Layer

This paper presents an innovative software-defined radio architecture for the real-time implementation of WiMAX transceivers. The architecture consists of commercially available field-programmable gate array and digital signal processor modules. We show ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

WiSec '10: Proceedings of the third ACM conference on Wireless network security

March 2010

186 pages

ISBN:9781605589237

DOI:10.1145/1741866

General Chair:
Susanne Wetzel
Stevens Institute of Technology, USA
,
Program Chairs:
Cristina Nita-Rotaru
Purdue University, USA
,
Frank Stajano
University of Cambridge, UK

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGSAC: ACM Special Interest Group on Security, Audit, and Control

In-Cooperation

SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 March 2010

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

WISEC '10

Sponsor:

SIGSAC

WISEC '10: Third ACM Conference on Wireless Network Security

March 22 - 24, 2010

New Jersey, Hoboken, USA

Acceptance Rates

Overall Acceptance Rate 98 of 338 submissions, 29%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

183
Total Citations
View Citations
1,438
Total Downloads

Downloads (Last 12 months)64
Downloads (Last 6 weeks)5

Reflects downloads up to 21 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Zhou QHe YYang KChi T(2024)Physical-Layer Identification of Wireless IoT Nodes Through PUF-Controlled Transmitter Spectral RegrowthIEEE Transactions on Microwave Theory and Techniques10.1109/TMTT.2023.330505572:2(1045-1055)Online publication date: Feb-2024
https://doi.org/10.1109/TMTT.2023.3305055
Wu CZeng Q(2024)Turning Noises to Fingerprint-Free “Credentials”: Secure and Usable Drone AuthenticationIEEE Transactions on Mobile Computing10.1109/TMC.2024.337350323:10(10161-10174)Online publication date: Oct-2024
https://doi.org/10.1109/TMC.2024.3373503
Pan QAn ZZhao XYang L(2024)The Power of Precision: High-Resolution Backscatter Frequency Drift in RFID IdentificationIEEE Transactions on Mobile Computing10.1109/TMC.2023.334768123:8(8370-8385)Online publication date: Aug-2024
https://doi.org/10.1109/TMC.2023.3347681
Joo KJo HChoi W(2024)Securing Passive Keyless Entry and Start System in Modern Vehicles Based on LF-Band Signal AnalysisIEEE Internet of Things Journal10.1109/JIOT.2024.345392011:24(40176-40190)Online publication date: 15-Dec-2024
https://doi.org/10.1109/JIOT.2024.3453920
Zhang ZWang YBai JXiao ZZhou H(2024)Uncovering the Authentic RF Fingerprint: Exploiting Random Window Slicing and Complex-Valued Network2024 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN60899.2024.10651357(1-8)Online publication date: 30-Jun-2024
https://doi.org/10.1109/IJCNN60899.2024.10651357
Hoang TVahid ASicker DSabharwal A(2024)Physical-Layer Spoofing in WiFi 6 to Steer the Beam Toward the AttackerICC 2024 - IEEE International Conference on Communications10.1109/ICC51166.2024.10622744(4006-4011)Online publication date: 9-Jun-2024
https://doi.org/10.1109/ICC51166.2024.10622744
Illi EQaraqe MAlthunibat SAlhasanat AAlsafasfeh Mde Ree MMantas GRodriguez JAman WAl-Kuwari S(2024)Physical Layer Security for Authentication, Confidentiality, and Malicious Node Detection: A Paradigm Shift in Securing IoT NetworksIEEE Communications Surveys & Tutorials10.1109/COMST.2023.332732726:1(347-388)Online publication date: Sep-2025
https://doi.org/10.1109/COMST.2023.3327327
Zhang SHuang WLiu Y(2024)A systematic survey on physical layer security oriented to reconfigurable intelligent surface empowered 6GComputers & Security10.1016/j.cose.2024.104100(104100)Online publication date: Sep-2024
https://doi.org/10.1016/j.cose.2024.104100
Tyler JFadul MHilling MReising DLoveless T(2024)Assessing adversarial replay and deep learning-driven attacks on specific emitter identification-based security approachesDiscover Internet of Things10.1007/s43926-024-00077-24:1Online publication date: 19-Nov-2024
https://doi.org/10.1007/s43926-024-00077-2
de Ree MDogan‐Tusha SIlli EQaraqe MAlthunibat SMantas GRodriguez J(2024) Physical Layer Security for RF ‐Based Massive IoT Security and Privacy for 6G Massive IoT10.1002/9781119988007.ch6(155-192)Online publication date: 13-Dec-2024
https://doi.org/10.1002/9781119988007.ch6
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents