Wed, May 15, 2024
[Archive]
Volume 15, Issue 1 (Special Issue on AI in ICT 2023)
2023, 15(1): 1-15 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Nopahari S, Gharaee H, Khademzadeh A. Selfish Node Detection Based on GA and Learning Automata in IoT. International Journal of Information and Communication Technology Research 2023; 15 (1) : 1
URL: http://ijict.itrc.ac.ir/article-1-535-en.html
URL: http://ijict.itrc.ac.ir/article-1-535-en.html
1- Computer engineering department, Science and Research Branch, Islamic Azad University Tehran, Iran
2- Iran Telecommunication Research Center (ITRC) Tehran, Iran , gharaee@itrc.ac.ir
3- Iran Telecommunication Research Center (ITRC) Tehran, Iran
2- Iran Telecommunication Research Center (ITRC) Tehran, Iran , gharaee@itrc.ac.ir
3- Iran Telecommunication Research Center (ITRC) Tehran, Iran
Abstract: (949 Views)
It is critical to increasing the network throughput on the internet of things with short-range nodes. Nodes prevent to cooperate with other nodes are known as selfish nodes. The proposed method for discovering the selfish node is based on genetic algorithm and learning automata. It consists of three phases of setup and clustering, the best routing selection based on genetic algorithm, and finally, the learning and update phase. The clustering algorithm implemented in the first phase. In the second phase, the neighbor node selected for forwarding the packet in which has a high value of fitness function. In the third phase, each node monitors its neighbor nodes and uses the learning automata system to identify the selfish nodes. The results of the simulation has shown the detection accuracy of selfish nodes in comparison with the existing methods average 10 %, and the false positive rate has decreased by 5 %.
Article number: 1
Keywords: Internet of Thing (IoT), selfish node, Genetic Algorithm (GA), Learning Automata (LA), Detection accuracy (DA), false positive rate (FPR).
References
1. [1] Balaji, S., Karan Nathani, and R. Santhakumar. (2019) "IoT technology, applications and challenges: a contemporary survey." Wireless personal communications : 363-388. [DOI:10.1007/s11277-019-06407-w]
2. [2] Kumar, Sachin, Prayag Tiwari, and Mikhail Zymbler. (2019) "Internet of Things is a revolutionary approach for future technology enhancement: a review." Journal of Big Data : 111. [DOI:10.1186/s40537-019-0268-2]
3. [3] Serpanos, Dimitrios, and Marilyn Wolf (2017)."Internet-ofthings (IoT) systems: architectures, algorithms, methodologies. Springer. [DOI:10.1007/978-3-319-69715-4_2]
4. [4] Aleksandrovičs, Vladislavs, Eduards Filičevs, and Jānis Kampars. (2016) "Internet of things: Structure, features and management." Information Technology and Management Science: 78-84. [DOI:10.1515/itms-2016-0015]
5. [5] Seyfollahi, Ali, Meysam Moodi, and Ali Ghaffari. "MFORPL: A secure RPL-based routing protocol utilizing mothflame optimizer for the IoT applications." Computer Standards & Interfaces 82 (2022): 103622. [DOI:10.1016/j.csi.2022.103622]
6. [6] Khattak, Hasan Ali, et al. (2019) "Perception layer security in Internet of Things." Future Generation Computer Systems:144-164. [DOI:10.1016/j.future.2019.04.038]
7. [7] Jafarian, Tohid, et al. "A survey and classification of the security anomaly detection mechanisms in software defined networks." Cluster Computing 24 (2021): 1235-1253.. [DOI:10.1007/s10586-020-03184-1]
8. [8] Nobahary, Solmaz, Hossein Gharaee Garakani, and Ahmad Khademzadeh. "Detecting Noncooperation Nodes Mechanisms in Wireless Networks: A Survey." Security and Communication Networks 2022 (2022). [DOI:10.1155/2022/6486816]
9. [9] Padiya, S. A. G. A. R., Rakesh Pandit, and Sachin Patel. (2013)"Survey of innovated techniques to detect selfish nodes in MANET." International Journal of Computer Networking, Wireless and Mobile Communications (IJCNWMC): 2250-1568.
10. [10] Samian, Normalia, et al. (2015) "Cooperation stimulation mechanisms for wireless multihop networks: A survey. Journal of Network and Computer Applications: 88-106. [DOI:10.1016/j.jnca.2015.04.012]
11. [11] O. León, J. Hernández-Serrano, and M. Soriano, (2010) "Outwitting smart selfish nodes in wireless mesh networks,"Int. J. Commun. Syst., vol. 23, no. 5, pp. 633-652. [DOI:10.1002/dac.1102]
12. [12] S. K. Das, P. S. Chatterjee, and M. Roy, (2014) "Detecting and Punishing the Selfish Node and Its Behavior in WSN," vol. 4, no. 2, pp. 11-15. [DOI:10.14445/22492593/IJCOT-V6P303]
13. [13] G. Rizwana and G. Wasim, (2015) "Enhanced Intrusion Detection & Prevention Mechanism for Selfishness in MANET," Int. J. Innov. Res. Comput. Commun. Eng., vol. 3,no. 10, pp. 10131-10138.
14. [14] C. Science and S. Engineering, (2015) "A Comparative Study of Selfish Node Detection Methods in Manet," Int. J. Adv. Res. Comput. Sci. Softw. Eng., vol. 5, no. 8, pp. 306-310.
15. [15] Nobahary, S., & Babaie, S. (2018). A Credit-based Method to Selfish Node Detection in Mobile Ad-hoc Network. Applied Computer Systems, 118-127. [DOI:10.2478/acss-2018-0015]
16. [16] T. S. A. Al-roubaiey, E. Shakshuki, and A. Mahmoud, (2009) "Video transmission enhancement in presence of misbehaving nodes in MANETs," pp. 273-282. [DOI:10.1007/s00530-009-0166-0]
17. [17] E. M. Shakshuki, S. Member, N. Kang, and T. R. Sheltami, (2013) "EAACK - A Secure Intrusion-Detection System for MANETs," vol. 60, no. 3, pp. 1089-1098. [DOI:10.1109/TIE.2012.2196010]
18. [18] M. Bounouni, (2018) "Acknowledgment-based punishment and stimulation scheme for mobile ad hoc network," J.Supercomput: 5373-5398 [DOI:10.1007/s11227-018-2434-2]
19. [19] Basar, Tamer, and Geert Jan Olsder. (1999) "Dynamic noncooperative game theory." Vol. 23. Siam. [DOI:10.1137/1.9781611971132]
20. [20] C. Vijayakumaran and T. A. Macriga, (2017) "An integrated game theoretical approach to detect misbehaving nodes in MANETs," Proc. 2017 2nd Int. Conf. Comput. Commun. Technol. ICCCT 2017, pp. 173-180. [DOI:10.1109/ICCCT2.2017.7972268]
21. [21] Nobahary, Solmaz, et al. (2019) "Selfish node detection based on hierarchical game theory in IoT." EURASIP Journal on Wireless Communications and Networking: 255. [DOI:10.1186/s13638-019-1564-4]
22. [22] I. Introduction, (2017) "A REVIEW ON NODE ACTIVITY DETECTION , SELFISH & MALICIOUS BEHAVIORALPATTERNS USING WATCHDOG," pp. 1-5.
23. [23] A. Lupia, C. A. Kerrache, and F. De Rango ( 2017) "TEEM : Trust-based Energy-Efficient Distributed Monitoring for Mobile Ad-hoc Networks," no. 1, pp. 133-135. [DOI:10.1109/WD.2017.7918128]
24. [24] Nobahary, Solmaz, et al. (2018) "DISOT: Distributed Selfish Node Detection in Internet of Things." International Journal of Information and Communication Technology Research: 19-30.
25. [25] A. Jesudoss, S. V. Kasmir Raja, and A. Sulaiman, (2015) "Stimulating truth-telling and cooperation among nodes in VANETs through payment and punishment scheme, Ad Hoc Networks, vol. 24, no. PA, pp. 250-253. [DOI:10.1016/j.adhoc.2014.08.018]
26. [26] Zhang, Wei, and et al. (2018) "A novel trust management scheme based on Dempster-Shafer evidence theory for malicious nodes detection in wireless sensor networks." The Journal of Supercomputing: 1779-1801. [DOI:10.1007/s11227-017-2150-3]
27. [27] Rani, Shalli, Syed Hassan Ahmed, and Ravi Rastogi. (2019)"Dynamic clustering approach based on wireless sensor networks genetic algorithm for IoT applications." Wireless Networks: 1-10. [DOI:10.1007/s11276-019-02083-7]
28. [28] Geetha V, Hariprasad S A, (2020) "A Conjectural based Framework to Detect & defend/Classify Selfish Nodes and Malicious Nodes in Manet Using AODV" International Journal of Innovations in Engineering and Technology (IJIET):8-14.
29. [29] Lin, Haifeng, and Fuquan Zhang. (2020) "A scheme for stimulating message relaying cooperation." International Journal of Distributed Sensor Networks: 1-8. [DOI:10.1177/1550147720907038]
30. [30] Susan K, Konyeha C, John-Otumu AM, Mughele ES (2020)" An Improved Token-Based Umpiring Technique for Detecting and Eliminating Selfish Nodes in Mobile Ad-hoc Networks." Egyptian Computer Science Journal: 1-12.
Send email to the article author
| Rights and permissions | |
 | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
