Cooperative Jamming for Physical Layer Security Enhancement Using Deep Reinforcement Learning

Sayed Amir Hoseini; Faycal Bouhafs; Neda Aboutorab; Parastoo Sadeghi; Frank den Hartog

doi:10.1109/GCWkshps58843.2023.10465104

Cooperative Jamming for Physical Layer Security Enhancement Using Deep Reinforcement Learning

Sayed Amir Hoseini, Faycal Bouhafs, Neda Aboutorab, Parastoo Sadeghi, Frank den Hartog

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

5 Citations (Scopus)

Abstract

Wireless data communications are always facing the risk of eavesdropping and interception. Conventional protection solutions which are based on encryption may not always be practical as is the case for wireless IoT networks or may soon become ineffective against quantum computers. In this regard, Physical Layer Security (PLS) presents a promising approach to secure wireless communications through the exploitation of the physical properties of the wireless channel. Cooperative Friendly Jamming (CFJ) is among the PLS techniques that have received attention in recent years. However, finding an optimal transmit power allocation that results in the highest secrecy is a complex problem that becomes more difficult to address as the size of the wireless network increases. In this paper, we propose an optimization approach to achieve CFJ in large Wi-Fi networks by using a Reinforcement Learning Algorithm. Obtained results show that our optimization approach offers better secrecy results and becomes more effective as the network size and the density of Wi-Fi access points increase.

Original language	English
Title of host publication	2023 IEEE Globecom Workshops, GC Wkshps 2023
Editors	José Roberto Boisson de Marca, Nelson Luis Saldanha da Fonseca, Stefano Bregni, Lisandro Zambenedetti Granville, Fabrizio Granelli, Christos Verikoukis, Shiwen Mao
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	1838-1843
Number of pages	6
ISBN (Electronic)	9798350370218
DOIs	https://doi.org/10.1109/GCWkshps58843.2023.10465104
Publication status	Published - 2023
Externally published	Yes
Event	2023 IEEE Globecom Workshops, GC Wkshps 2023 - Kuala Lumpur, Malaysia Duration: 4 Dec 2023 → 8 Dec 2023

Publication series

Name	2023 IEEE Globecom Workshops, GC Wkshps 2023

Conference

Conference	2023 IEEE Globecom Workshops, GC Wkshps 2023
Country/Territory	Malaysia
City	Kuala Lumpur
Period	4/12/23 → 8/12/23

Access to Document

10.1109/GCWkshps58843.2023.10465104

Cite this

Hoseini, S. A., Bouhafs, F., Aboutorab, N., Sadeghi, P., & den Hartog, F. (2023). Cooperative Jamming for Physical Layer Security Enhancement Using Deep Reinforcement Learning. In J. R. B. de Marca, N. L. S. da Fonseca, S. Bregni, L. Zambenedetti Granville, F. Granelli, C. Verikoukis, & S. Mao (Eds.), 2023 IEEE Globecom Workshops, GC Wkshps 2023 (pp. 1838-1843). (2023 IEEE Globecom Workshops, GC Wkshps 2023). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/GCWkshps58843.2023.10465104

Hoseini, Sayed Amir ; Bouhafs, Faycal ; Aboutorab, Neda et al. / Cooperative Jamming for Physical Layer Security Enhancement Using Deep Reinforcement Learning. 2023 IEEE Globecom Workshops, GC Wkshps 2023. editor / José Roberto Boisson de Marca ; Nelson Luis Saldanha da Fonseca ; Stefano Bregni ; Lisandro Zambenedetti Granville ; Fabrizio Granelli ; Christos Verikoukis ; Shiwen Mao. IEEE, Institute of Electrical and Electronics Engineers, 2023. pp. 1838-1843 (2023 IEEE Globecom Workshops, GC Wkshps 2023).

@inproceedings{42acb6e06d084ccb8e18085792ac9855,

title = "Cooperative Jamming for Physical Layer Security Enhancement Using Deep Reinforcement Learning",

abstract = "Wireless data communications are always facing the risk of eavesdropping and interception. Conventional protection solutions which are based on encryption may not always be practical as is the case for wireless IoT networks or may soon become ineffective against quantum computers. In this regard, Physical Layer Security (PLS) presents a promising approach to secure wireless communications through the exploitation of the physical properties of the wireless channel. Cooperative Friendly Jamming (CFJ) is among the PLS techniques that have received attention in recent years. However, finding an optimal transmit power allocation that results in the highest secrecy is a complex problem that becomes more difficult to address as the size of the wireless network increases. In this paper, we propose an optimization approach to achieve CFJ in large Wi-Fi networks by using a Reinforcement Learning Algorithm. Obtained results show that our optimization approach offers better secrecy results and becomes more effective as the network size and the density of Wi-Fi access points increase.",

keywords = "Artificial Noise, Friendly Jamming, Machine Learning, Physical-Layer Security, Programmable Networks, Reinforcement Learning, SDN, Secrecy",

author = "Hoseini, {Sayed Amir} and Faycal Bouhafs and Neda Aboutorab and Parastoo Sadeghi and {den Hartog}, Frank",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE Globecom Workshops, GC Wkshps 2023 ; Conference date: 04-12-2023 Through 08-12-2023",

year = "2023",

doi = "10.1109/GCWkshps58843.2023.10465104",

language = "English",

series = "2023 IEEE Globecom Workshops, GC Wkshps 2023",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

pages = "1838--1843",

editor = "{de Marca}, {Jos{\'e} Roberto Boisson } and {da Fonseca}, {Nelson Luis Saldanha} and Bregni, {Stefano } and {Zambenedetti Granville}, {Lisandro } and Granelli, {Fabrizio } and Verikoukis, {Christos } and Mao, {Shiwen }",

booktitle = "2023 IEEE Globecom Workshops, GC Wkshps 2023",

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Hoseini, SA, Bouhafs, F, Aboutorab, N, Sadeghi, P & den Hartog, F 2023, Cooperative Jamming for Physical Layer Security Enhancement Using Deep Reinforcement Learning. in JRB de Marca, NLS da Fonseca, S Bregni, L Zambenedetti Granville, F Granelli, C Verikoukis & S Mao (eds), 2023 IEEE Globecom Workshops, GC Wkshps 2023. 2023 IEEE Globecom Workshops, GC Wkshps 2023, IEEE, Institute of Electrical and Electronics Engineers, pp. 1838-1843, 2023 IEEE Globecom Workshops, GC Wkshps 2023, Kuala Lumpur, Malaysia, 4/12/23. https://doi.org/10.1109/GCWkshps58843.2023.10465104

Cooperative Jamming for Physical Layer Security Enhancement Using Deep Reinforcement Learning. / Hoseini, Sayed Amir; Bouhafs, Faycal; Aboutorab, Neda et al.
2023 IEEE Globecom Workshops, GC Wkshps 2023. ed. / José Roberto Boisson de Marca; Nelson Luis Saldanha da Fonseca; Stefano Bregni; Lisandro Zambenedetti Granville; Fabrizio Granelli; Christos Verikoukis; Shiwen Mao. IEEE, Institute of Electrical and Electronics Engineers, 2023. p. 1838-1843 (2023 IEEE Globecom Workshops, GC Wkshps 2023).

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

TY - GEN

T1 - Cooperative Jamming for Physical Layer Security Enhancement Using Deep Reinforcement Learning

AU - Hoseini, Sayed Amir

AU - Bouhafs, Faycal

AU - Aboutorab, Neda

AU - Sadeghi, Parastoo

AU - den Hartog, Frank

PY - 2023

Y1 - 2023

N2 - Wireless data communications are always facing the risk of eavesdropping and interception. Conventional protection solutions which are based on encryption may not always be practical as is the case for wireless IoT networks or may soon become ineffective against quantum computers. In this regard, Physical Layer Security (PLS) presents a promising approach to secure wireless communications through the exploitation of the physical properties of the wireless channel. Cooperative Friendly Jamming (CFJ) is among the PLS techniques that have received attention in recent years. However, finding an optimal transmit power allocation that results in the highest secrecy is a complex problem that becomes more difficult to address as the size of the wireless network increases. In this paper, we propose an optimization approach to achieve CFJ in large Wi-Fi networks by using a Reinforcement Learning Algorithm. Obtained results show that our optimization approach offers better secrecy results and becomes more effective as the network size and the density of Wi-Fi access points increase.

AB - Wireless data communications are always facing the risk of eavesdropping and interception. Conventional protection solutions which are based on encryption may not always be practical as is the case for wireless IoT networks or may soon become ineffective against quantum computers. In this regard, Physical Layer Security (PLS) presents a promising approach to secure wireless communications through the exploitation of the physical properties of the wireless channel. Cooperative Friendly Jamming (CFJ) is among the PLS techniques that have received attention in recent years. However, finding an optimal transmit power allocation that results in the highest secrecy is a complex problem that becomes more difficult to address as the size of the wireless network increases. In this paper, we propose an optimization approach to achieve CFJ in large Wi-Fi networks by using a Reinforcement Learning Algorithm. Obtained results show that our optimization approach offers better secrecy results and becomes more effective as the network size and the density of Wi-Fi access points increase.

KW - Artificial Noise

KW - Friendly Jamming

KW - Machine Learning

KW - Physical-Layer Security

KW - Programmable Networks

KW - Reinforcement Learning

KW - SDN

KW - Secrecy

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UR - https://ieeexplore.ieee.org/xpl/conhome/10464388/proceeding

UR - https://globecom2023.ieee-globecom.org/

U2 - 10.1109/GCWkshps58843.2023.10465104

DO - 10.1109/GCWkshps58843.2023.10465104

M3 - Conference contribution

AN - SCOPUS:85190256816

T3 - 2023 IEEE Globecom Workshops, GC Wkshps 2023

SP - 1838

EP - 1843

BT - 2023 IEEE Globecom Workshops, GC Wkshps 2023

A2 - de Marca, José Roberto Boisson

A2 - da Fonseca, Nelson Luis Saldanha

A2 - Bregni, Stefano

A2 - Zambenedetti Granville, Lisandro

A2 - Granelli, Fabrizio

A2 - Verikoukis, Christos

A2 - Mao, Shiwen

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - 2023 IEEE Globecom Workshops, GC Wkshps 2023

Y2 - 4 December 2023 through 8 December 2023

ER -

Hoseini SA, Bouhafs F, Aboutorab N, Sadeghi P, den Hartog F. Cooperative Jamming for Physical Layer Security Enhancement Using Deep Reinforcement Learning. In de Marca JRB, da Fonseca NLS, Bregni S, Zambenedetti Granville L, Granelli F, Verikoukis C, Mao S, editors, 2023 IEEE Globecom Workshops, GC Wkshps 2023. IEEE, Institute of Electrical and Electronics Engineers. 2023. p. 1838-1843. (2023 IEEE Globecom Workshops, GC Wkshps 2023). doi: 10.1109/GCWkshps58843.2023.10465104

Cooperative Jamming for Physical Layer Security Enhancement Using Deep Reinforcement Learning

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