RF-WAVEGUARD: Enhancing UAV Security Against Signal Jamming Attacks through Radio Frequency Watermarking
June 2024
Pages 71 - 80
Abstract
As Unmanned Aerial Vehicles (UAVs) become increasingly integral to a variety of industries, their dependency on radio frequency (RF) signal-based communication systems has exposed them to a multitude of security vulnerabilities. One of the most notable ones is RF jamming, which can disrupt communication, control, and navigation. While traditional countermeasures, such as Hardware Sandboxing \citemead_defeating_2016, or Intrusion Detection System (IDS) based on Deep Learning aim to mitigate these threats, they exhibit limitations in addressing sophisticated jamming attacks \citedhomane_counter_measures_2020-1. This paper presents a novel design of an authentication-based strategy using RF watermarking. Our proposed RF watermarking technique embeds hidden identifiers within RF signals to authenticate communication sources and detect jamming attempts. Through a comprehensive evaluation, we demonstrate the effectiveness of our proposed scheme in enhancing UAV communication security and ensuring reliable operation in the presence of adversarial interference.
References
[1]
A. Ahmed, Q. Ahmed, A. Rehman, and S. Karim. 2012. The Performance of Fast Frequency Hopping System in Additive White Gaussian Noise (AWGN). International Journal of Computer Applications, Vol. 46, 20, 14--22.
[2]
N. A. S. Al-Maweri, A. Q. M. Sabri, A. M. Mansoor, U. H. Obaidellah, E. R. M. Faizal, and J. C. Lai P. 2017. Metadata Hiding for UAV Video Based on Digital Watermarking in DWT Transform. Multimedia Tools and Applications, Vol. 76, 15, 16239--16261.
[3]
M. Aref, S. Jayaweera, and E. Yepez. 2020. A Survey on Cognitive Anti-jamming Communications. IET Communications, Vol. 14.
[4]
R. Beaulieu, S. Treatman-Clark, D. Shors, B. Weeks, J. Smith, and L. Wingers. 2015. The SIMON and SPECK Lightweight Block Ciphers. In Proceedings of the 52nd Annual Design Automation Conference. ACM/EDAC/IEEE, San Francisco, CA, USA, 1--6.
[5]
A. Brito, P. Sebastião, and N. Souto. 2019. Jamming for Unauthorized UAV Operations-Communications Link. In Proceedings of the 2019 International Young Engineers Forum (YEF-ECE) (Costa de Caparica, Portugal). IEEE, 94--98.
[6]
V. Chamola, P. Kotesh, A. Agarwal, Naren, N. Gupta, and M. Guizani. 2021. A Comprehensive Review of Unmanned Aerial Vehicle Attacks and Neutralization Techniques. Ad Hoc Networks, Vol. 111, 102324.
[7]
K. J. Devi, P. Singh, M. Bilal, and A. Nayyar. 2024. Enabling Secure Image Transmission in Unmanned Aerial Vehicle Using Digital Image Watermarking with H-Grey Optimization. Expert Systems with Applications, Vol. 236, 121190.
[8]
P. Dhomane and R. Mathew. 2020. Counter-Measures to Spoofing and Jamming of Drone Signals. SSRN Electronic Journal.
[9]
R. Di Pietro, G. Oligeri, and P. Tedeschi. 2019. JAM-ME: Exploiting Jamming to Accomplish Drone Mission. In Proceedings of the 2019 IEEE Conference on Communications and Network Security (CNS). 1--9.
[10]
H. Imai and S. Hirakawa. 1977. A New Multilevel Coding Method Using Error-Correcting Codes. IEEE Transactions on Information Theory, Vol. 23, 3, 371--377.
[11]
J. E. Kleider, S. Gifford, S. Chuprun, and B. Fette. 2004. Radio Frequency Watermarking for OFDM Wireless Networks. In Proceedings of the 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, Vol. 5. V--397.
[12]
A. Krayani, A. S. Alam, L. Marcenaro, A. Nallanathan, and C. Regazzoni. 2022. Automatic Jamming Signal Classification in Cognitive UAV Radios. IEEE Transactions on Vehicular Technology, Vol. 71, 12, 12972--12988.
[13]
F. Lakew Yihunie, A. K. Singh, and S. Bhatia. 2020. Assessing and Exploiting Security Vulnerabilities of Unmanned Aerial Vehicles. In Smart Systems and IoT: Innovations in Computing, ( Vol. 160), Springer, 701--710.
[14]
Z. Lei, P. Ding, W. Zheng, X. Fei, and H. Fan. 2021. UAV Countermeasure Technology Based on Partial-band Noise Jamming. In Proceedings of the 2021 33rd Chinese Control and Decision Conference (CCDC). 1456--1461.
[15]
Y. Li, J. Pawlak, J. Price, K. Al Shamaileh, Q. Niyaz, S. Paheding, and V. Devabhaktuni. 2022. Jamming Detection and Classification in OFDM-Based UAVs via Feature- and Spectrogram-Tailored Machine Learning. IEEE Access, Vol. 10, 16859--16870.
[16]
D. T. Magill, F. D. Natali, and G. P. Edwards. 1994. Spread-Spectrum Technology for Commercial Applications. Proc. IEEE, Vol. 82, 4, 572--584.
[17]
M. P. Marcinak and B. G. Mobasseri. 2005. Digital Video Watermarking for Metadata Embedding in UAV Video. In Proceedings of the MILCOM 2005 - 2005 IEEE Military Communications Conference. 1637--1643 Vol. 3.
[18]
J. Mead, C. Bobda, and T. JL Whitaker. [n.,d.]. Defeating drone jamming with hardware sandboxing. In 2016 IEEE Asian Hardware-Oriented Security and Trust (AsianHOST) (2016--12). 1--6.
[19]
J. Mikulka and S. Hanus. 2007. CCK and Barker Coding Implementation in IEEE 802.11b Standard. In Proc. of the 2007 17th International Conference Radioelektronika. 1--4.
[20]
S. A. H. Mohsan, N. Q. H. Othman, Y. Li, M. H. Alsharif, and M. A. Khan. 2023. Unmanned Aerial Vehicles (UAVs): Practical Aspects, Applications, Open Challenges, Security Issues, and Future Trends. Intelligent Service Robotics, Vol. 16, 1, 109--137.
[21]
S. Sciancalepore, F. Kusters, N. K. Abdelhadi, and G. Oligeri. 2023. Jamming Detection in Low-BER Mobile Indoor Scenarios via Deep Learning. IEEE Internet of Things Journal, 1--1.
[22]
J. Winters. 1987. On the Capacity of Radio Communication Systems with Diversity in a Rayleigh Fading Environment. IEEE Journal on Selected Areas in Communications, Vol. 5, 5, 871--878.
[23]
J. Xu, H. Lou, W. Zhang, and G. Sang. 2020. An Intelligent Anti-Jamming Scheme for Cognitive Radio Based on Deep Reinforcement Learning. IEEE Access, Vol. 8, 202563--202572. io
Index Terms
- RF-WAVEGUARD: Enhancing UAV Security Against Signal Jamming Attacks through Radio Frequency Watermarking
Recommendations
Jamming attacks and defenses for fast association in IEEE 802.11ah networks
AbstractTo reduce network congestion, most fast association mechanisms in 802.11ah networks control the number of devices to associate each round based on the management queue size. However, the management queue can be manipulated easily by ...
Inferring distributed reflection denial of service attacks from darknet
This work proposes a novel approach to infer and characterize Internet-scale DNS Distributed Reflection Denial of Service (DRDoS) attacks by leveraging the darknet space. Complementary to the pioneer work on inferring Distributed Denial of Service (DDoS)...
An Adaptable Module for Designing Jamming Attacks in WiFi Networks for ns-3
MSWiM '22: Proceedings of the 25th International ACM Conference on Modeling Analysis and Simulation of Wireless and Mobile SystemsThe inherent openness of wireless communication techniques has made them vulnerable to jamming attacks. However, the effectiveness of a jamming attack depends on numerous parameters and varies according to the state of the environment. At the same time, ...
Comments
Information & Contributors
Information
Published In
June 2024
97 pages
ISBN:9798400705557
DOI:10.1145/3643650
- Program Chairs:
- Maanak Gupta,
- Mahmoud Abdelsalam,
- Mir Pritom,
- Feras Awaysheh
Copyright © 2024 Owner/Author.
This work is licensed under a Creative Commons Attribution International 4.0 License.
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 19 June 2024
Check for updates
Author Tags
Qualifiers
- Research-article
Funding Sources
- The Italian Ministry for Universities and Research (MUR)
Conference
CODASPY '24
Sponsor:
CODASPY '24: Fourteenth ACM Conference on Data and Application Security and Privacy
June 21, 2024
Porto, Portugal
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 8Total Downloads
- Downloads (Last 12 months)8
- Downloads (Last 6 weeks)8
Other Metrics
Citations
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in