short-paper

Secure Routing in Multi-hop IoT-based Cognitive Radio Networks under Jamming Attacks

Authors:

Haythem Bany Salameh,

Moayad Aloqaily,

Azzedine BoukercheAuthors Info & Claims

MSWIM '19: Proceedings of the 22nd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

Pages 323 - 327

https://doi.org/10.1145/3345768.3355944

Published: 25 November 2019 Publication History

Abstract

Integrating Cognitive Radio (CR) technology in Internet-of-Things (IoT) devices allows efficient large-scale deployment of IoT systems. Recently, research efforts are shifted toward adopting CR in IoT as a response for the spectrum scarcity problem. Unfortunately, CR Networks (CRNs) share the same security weaknesses with traditional wireless networks. CR communication is also vulnerable to jamming attacks which can significantly affect network performance, consume network resources and results in delays, that make it less suitable for IoT time-critical systems. Routing in CR-based IoT networks, in general, considered as a challenging issue. Under the jamming attack, routing becomes even more challenging. In this paper, we introduce a new jamming-aware routing and channel assignment protocol that deals with proactive jamming attacks in CR-based IoT networks without requiring extra resources. The proposed protocol attempts at improving the overall packet delivery ratio in the network while considering the primary user's activities, multi-channel fading and jamming behavior. The proposed protocol consists of three phases: route discovery, channel assignment, and path selection. The channel assignment problem along each path is formulated as an optimization problem with the objective of maximizing the end-to-end probability of success. This problem is shown to be an uni-modular problem, which can be solved in polynomial-time using linear programming techniques. Compared to reference protocols, simulation results reveal that the proposed protocol significantly improves network performance in terms of packet delivery ratio.

References

[1]

l Ridhawi, Ismaeel, et al. "A Profitable and Energy-Efficient Cooperative Fog Solution for IoT Services." IEEE Transactions on Industrial Informatics (2019).

[2]

. Balasubramanian, F. Zaman, M. Aloqaily, I. A. Ridhawi, Y. Jararweh and H. B. Salameh, "A Mobility Management Architecture for Seamless Delivery of 5G-IoT Services," ICC 2019 - 2019 IEEE International Conference on Communications (ICC), Shanghai, China, 2019, pp. 1--7.

[3]

. Singh, G. Tripathi, and A. J. Jara, "A survey of Internet-of-Things: Future vision, architecture, challenges and services,"s in Proc. IEEE World Forum Internet Things, Mar. 2014, pp. 287--292.

[4]

. A. Khan, M. H. Rehmani, and A. Rachedi, $“$When Cognitive Radio Meets the Internet of Things,$"$ IEEE 12th Int'l. Wireless Commun. $&$ Mobile Computing Conf., Paphos, Cyprus, Sept. 5--9 2016.

[5]

loqaily, Moayad, et al. "An intrusion detection system for connected vehicles in smart cities." Ad Hoc Networks 90 (2019): 101842.

[6]

Lu, W. Wang, and C. Wang, $“$Modeling, evaluation and detection of jamming attacks in time-critical wireless applications,$"$ IEEE Transactions on Mobile Computing, Vol. 13, No. 8, pp. 1746--1759, 2014.

[7]

. Mourougayane and S. Srikanth, $“$Intelligent jamming threats to cognitive radio based strategic communication networks - a survey,$"$ in 2015 3rd International Conference on Signal Processing, Communication and Networking (ICSCN), March 2015, pp. 1--6.

[8]

Bany Salameh, S. Almajali, M. Ayyash and H. Elgala, $“$Spectrum assignment in cognitive radio networks for internet-of-things delaysensitive applications under jamming attacks,$"$ IEEE Internet of Things Journal, vol. 5, no. 3, pp. 1903--1913, June 2018.

[9]

toum, Safa, Burak Kantarci, and Hussein T. Mouftah. "Detection of known and unknown intrusive sensor behavior in critical applications." IEEE Sensors Letters 1.5 (2017): 1--4.

[10]

alehi, M., & Boukerche, A. (2019). Secure opportunistic routing protocols: methods, models, and classification. Wireless Networks, 25(2), 559--571.

[11]

. Rawi and K. Yau, $“$Route selection for minimizing interference to primary users in cognitive radio networks: A reinforcement learning approach,$"$ in Proc. IEEE Symp. Comput. Intell. Commun. Syst. Netw., Singapore, 2013, pp. 24--30.

[12]

. Khalife, S. Ahuja, N. Malouch, and M. Krunz, $“$Probabilistic path selection in opportunistic cognitive radio networks$"$, in Proc. IEEE GlobeCom, 2008, pp. 1--5.

[13]

El-Sherif and A. Mohamed, $“$Joint routing and resource allocation for delay minimization in cognitive radio based mesh networks,$"$ IEEE Trans. Wireless Commun., vol. 13, no. 1, pp. 186--197, Jan. 2014.

[14]

. Kaushik, Y. Yoganandam i S.K. Sahoo, $“$Quality and Availability of spectrum based routing for Cognitive radio enabled IoT networks$"$, Journal of Communications Software and Systems, vol.14, br. 3, str. 239--248, 2018.

[15]

. Chowdhury and M. Di Felice, $“$Search: A routing protocol for mobile cognitive radio ad-hoc networks,$"$ in Sarnoff Symposium, 2009. SARNOFF '09. IEEE, 2009, pp. 1--6.

[16]

. Ji, M. Yan, R. Beyah and Z. Cai, "Semi-Structure Routing and Analytical Frameworks for Cognitive Radio Networks," in IEEE Transactions on Mobile Computing, vol. 15, no. 4, pp. 996--1008, 1.

[17]

. Otoum, B. Kantarci and H. Mouftah, "Empowering Reinforcement Learning on Big Sensed Data for Intrusion Detection," ICC 2019 - 2019 IEEE International Conference on Communications (ICC), Shanghai, China, 2019, pp. 1--7.

[18]

. Otoum, B. Kantarci and H. Mouftah, "Empowering Reinforcement Learning on Big Sensed Data for Intrusion Detection," ICC 2019 - 2019 IEEE International Conference on Communications (ICC), Shanghai, China, 2019, pp. 1--7.

[19]

toum, Safa, Burak Kantarci, and Hussein T. Mouftah. "On the feasibility of deep learning in sensor network intrusion detection." IEEE Networking Letters 1.2 (2019): 68--71.

[20]

Manogna and K. Naik, $“$Detection of Jamming Attack in Cognitive Radio Networks$"$, International Journal of Recent Advances in Engineering $&$ Technology (IJRAET), Vol. 2, Issue 6, pp. 69--72, 2014.

[21]

. Xiao, T. Chen, J. Liu, and H. Dai, $“$Anti-jamming transmission stackelberg game with observation errors,$"$ Communications Letters, IEEE, vol. 19, no. 6, pp. 949--952, June 2015.

[22]

. Adem and B. Hamdaoui, $“$Jamming resiliency and mobility management in cognitive communication networks$"$, in Proc. of the IEEE International Conference on Communications (ICC), May 2017

[23]

hamayseh, Yaser, et al. "Dynamic framework to mining Internet of Things for multimedia services." Expert Systems (2019): e12404.

[24]

loqaily, Moayad, et al. "Data and service management in densely crowded environments: Challenges, opportunities, and recent developments." IEEE Communications Magazine 57.4 (2019): 81--87.

[25]

. Wu, B. Wang, and K. Liu, $“$Optimal defense against jamming attacks in cognitive radio networks using the Markov decision process approach$"$, in Proc. of the IEEE Globecom Conference, 2010

[26]

Bany Salameh, $"$ Rate-Maximization Channel Assignment Scheme for Cognitive Radio Networks,$"$ in IEEE Global Telecommunications Conference GLOBECOM'10, Miami, FL, 2010, pp. 1--5.

Cited By

Darabkh KAl-Tahaineh MSwidan A(2024)JCARP: Joint Channel Assignment and Routing Protocol for cognitive-radio-based internet of things (CRIoT)Journal of Information and Telecommunication10.1080/24751839.2024.23245588:4(490-530)Online publication date: 13-Mar-2024
https://doi.org/10.1080/24751839.2024.2324558
Alotaibi B(2023)A Survey on Industrial Internet of Things Security: Requirements, Attacks, AI-Based Solutions, and Edge Computing OpportunitiesSensors10.3390/s2317747023:17(7470)Online publication date: 28-Aug-2023
https://doi.org/10.3390/s23177470
Musa AHalloush RSalamah HAwwad RAlnabelsi SBenkhelifa E(2023)Routing in FD-Enabled Cognitive Radio Networks with Minimum Time-Sharing for Improved Performance2023 Tenth International Conference on Software Defined Systems (SDS)10.1109/SDS59856.2023.10329248(126-130)Online publication date: 23-Oct-2023
https://doi.org/10.1109/SDS59856.2023.10329248
Show More Cited By

Index Terms

Secure Routing in Multi-hop IoT-based Cognitive Radio Networks under Jamming Attacks
1. Networks
  1. Network protocols

Recommendations

Intelligent jamming-aware routing in multi-hop IoT-based opportunistic cognitive radio networks
Abstract
Cognitive Radio Networks (CRNs) have emerged as a promising next-generation network technology that solves the spectrum scarcity issue and improves spectrum utilization. It is designed to help grant access for unlicensed users and ...
Attacks and countermeasures in multi-hop Cognitive Radio Networks

In Cognitive Radio Networks (CRNs), there are some new attacks. For instance, an attacker may modify the air interface of a CRN to mimic primary signal's characteristics, thereby causing legitimate Secondary Users (SUs) to erroneously identify the ...
Multi-agent learning based routing for delay minimization in Cognitive Radio Networks

To overcome the problem of underutilizing licensed spectrum, Cognitive Radio Networks (CRNs) have emerged in which Secondary Users (SUs) are allowed to access opportunistically the licensed spectrum allocated exclusively to Primary Users (PUs). In the ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

MSWIM '19: Proceedings of the 22nd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

November 2019

340 pages

ISBN:9781450369046

DOI:10.1145/3345768

General Chair:
Antonio A. F. Loureiro
Federal University of Minas Gerais, Brazil
,
Program Chairs:
Salil Kanhere
University of New South Wales, Australia
,
Paolo Bellavista
University of Bologna, Italy

Copyright © 2019 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

SIGSIM: ACM Special Interest Group on Simulation and Modeling

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 November 2019

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Short-paper

Conference

MSWiM '19

Sponsor:

SIGSIM

MSWiM '19: 22nd Int'l ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

November 25 - 29, 2019

FL, Miami Beach, USA

Acceptance Rates

Overall Acceptance Rate 398 of 1,577 submissions, 25%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

13
Total Citations
View Citations
160
Total Downloads

Downloads (Last 12 months)13
Downloads (Last 6 weeks)1

Reflects downloads up to 03 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Darabkh KAl-Tahaineh MSwidan A(2024)JCARP: Joint Channel Assignment and Routing Protocol for cognitive-radio-based internet of things (CRIoT)Journal of Information and Telecommunication10.1080/24751839.2024.23245588:4(490-530)Online publication date: 13-Mar-2024
https://doi.org/10.1080/24751839.2024.2324558
Alotaibi B(2023)A Survey on Industrial Internet of Things Security: Requirements, Attacks, AI-Based Solutions, and Edge Computing OpportunitiesSensors10.3390/s2317747023:17(7470)Online publication date: 28-Aug-2023
https://doi.org/10.3390/s23177470
Musa AHalloush RSalamah HAwwad RAlnabelsi SBenkhelifa E(2023)Routing in FD-Enabled Cognitive Radio Networks with Minimum Time-Sharing for Improved Performance2023 Tenth International Conference on Software Defined Systems (SDS)10.1109/SDS59856.2023.10329248(126-130)Online publication date: 23-Oct-2023
https://doi.org/10.1109/SDS59856.2023.10329248
Khasawneh MAzab AAlrabaee SSakkal HBakhit H(2023)Convergence of IoT and Cognitive Radio Networks: A Survey of Applications, Techniques, and ChallengesIEEE Access10.1109/ACCESS.2023.329409111(71097-71112)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3294091
Rugo AArdagna CIoini N(2022)A Security Review in the UAVNet Era: Threats, Countermeasures, and Gap AnalysisACM Computing Surveys10.1145/348527255:1(1-35)Online publication date: 17-Jan-2022
https://dl.acm.org/doi/10.1145/3485272
Cicioğlu MÇalhan AMiah M(2022)An effective routing algorithm for spectrum allocations in cognitive radio based internet of thingsConcurrency and Computation: Practice and Experience10.1002/cpe.736834:28Online publication date: 9-Oct-2022
https://doi.org/10.1002/cpe.7368
Derbas RBariah LMuhaidat SSofotasios PSaleh HDamiani E(2021)Battery Recharging Time-Based Routing for Power Constrained IoT Networks2021 4th International Conference on Advanced Communication Technologies and Networking (CommNet)10.1109/CommNet52204.2021.9641956(1-5)Online publication date: 3-Dec-2021
https://doi.org/10.1109/CommNet52204.2021.9641956
Siddiqui ABoukerche A(2021)Adaptive ensembles of autoencoders for unsupervised IoT network intrusion detectionComputing10.1007/s00607-021-00912-2Online publication date: 20-Feb-2021
https://doi.org/10.1007/s00607-021-00912-2
Yang RZhou ZTseng LAloqaily MBoukerche A(2020)Efficient and Robust Top-k Algorithms for Big Data IoTICC 2020 - 2020 IEEE International Conference on Communications (ICC)10.1109/ICC40277.2020.9148639(1-6)Online publication date: Jun-2020
https://doi.org/10.1109/ICC40277.2020.9148639
Haseeb KAlmustafa KJan ZSaba TTariq U(2020)Secure and Energy-Aware Heuristic Routing Protocol for Wireless Sensor NetworkIEEE Access10.1109/ACCESS.2020.30222858(163962-163974)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3022285
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.

Figures

Tables

Media

View Table of Conten