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Recent Advances in Computer Science and Communications

Editor-in-Chief

ISSN (Print): 2666-2558
ISSN (Online): 2666-2566

General Research Article

Mobile Ad Hoc Network Security Using Mean Field Game Theoretic Threshold-Based Scheme

Author(s): Khyati Chopra*

Volume 15, Issue 3, 2022

Published on: 04 September, 2020

Article ID: e180322185563 Pages: 9

DOI: 10.2174/2666255813999200904112438

Price: $65

Abstract

Background: Mobile Ad hoc Networks (MANET’s) have recently attracted attention as it is independent of any pre-existing network infrastructure or centralized administration. Security in MANET’s thus becomes a major concern due to its open and dynamic architecture.

Objectives: We have introduced a dynamic mean field game theoretic approach to enable an individual node in MANETs to make strategic security defense decisions without centralized administration.

Methods: The nodes in MANET’s act as a router to forward data packets and exchange routing information. Ad-hoc On demand Distance Vector (AODV) protocol is one of the standard MANET routing protocols which can be easily attacked by the fraudulent nodes. The fraudulent nodes can be deceptive and mislead the transmission of data packets in the network by providing shorter path and highest destination sequence number. Game theory finds wide application as a statistical and mathematical tool to model such dynamic networks and provide security.

Results: We have implemented mean field game theory for addressing security issue in MANET’s. Each node in this dynamic distributed network knows the information about its own state as well as the average reflection of the whole mean field. The players can strategically make distributed security defense decisions under adverse conditions. Unlike static threshold-based scheme for security, the threshold is estimated dynamically in this study. Each node checks whether the received Route REPly (RREP) sequence number is higher than a dynamically updated threshold value.

Conclusion: The comparative performance analysis of Throughput (TR), Packet Delivery Rate (PDR) and Average Cost (AC) has been demonstrated. Game theory has a vital role to validate and justify the intuitive strategic actions taken by each player to maximize their utility by playing optimal strategy. On the basis of the dynamic threshold calculated, the higher throughput and PDR could be achieved by eliminating the misleading paths. Simulation results corroborate that our dynamic mean field game theoretic scheme outperforms the static scheme.

Discussion: A dynamic approach for mobile ad hoc networks is presented in this paper to improve the performance of the network in hostile environment. We have introduced a dynamic mean field game theoretic approach to enable an individual node in MANETs to make strategic security defense decisions without centralized administration. In this dynamic distributed network, each node in the proposed scheme only needs to know its own state information and the average reflection of the whole mean field.

Keywords: Mean field game, security, Mobile Ad hoc Network (MANET), AODV, threshold-based, Intrusion Detection System (IDS)

Graphical Abstract

[1]
M. Liu, N. Patwari, and A. Terzis, "Special issue on sensor network applications", Proc. IEEE, vol. 98, no. 11, pp. 1804-1807, Nov 2010.
[http://dx.doi.org/10.1109/JPROC.2010.2068390]
[2]
P. Corke, T. Wark, R. Jurdak, W. Hu, P. Valencia, and D. Moore, "Environmental wireless sensor networks", Proc. IEEE, vol. 98, no. 11, pp. 1903-1917, Oct 2010.
[http://dx.doi.org/10.1109/JPROC.2010.2068530]
[3]
S.A. Munir, B. Ren, W. Jiao, B. Wang, D. Xie, and J. Ma, "Mobile wireless sensor network: Architecture and enabling technologies for ubiquitous computing", In Proceeding 21st International Conference on Advanced Information Networking and Applications Workshops, vol. 2, pp. 113-120, 2007.
[http://dx.doi.org/10.1109/AINAW.2007.257]
[4]
T. Das, and S. Roy, "Coordination based motion control in mobile wireless sensor network", In Proceeding IEEE International Conference on Electronic Systems, Signal Processing and Computing Technologies, 2014pp. 231-236
[http://dx.doi.org/10.1109/ICESC.2014.45]
[5]
X. Chen, and P. Yu, "Research on hierarchical mobile wireless sensor network architecture with mobile sensor nodes", In Proceeding IEEE 3rd International Conference on Biomedical Engineering and Informatics (BMEI), vol. 7, pp. 2863-2867, 2010.
[http://dx.doi.org/10.1109/BMEI.2010.5639549]
[6]
M. Javed, K. Zen, H.B. Lenando, and H. Zen, "Performance evaluation of beacon enabled IEEE 802.15. 4 MAC for mobile wireless sensor networks under NS-2", In: Proceeding IEEE 8th International Conference on Information Technology in Asia (CITA), 2013, pp. 1-7.
[7]
L. Wan, G. Han, L. Shu, N. Feng, C. Zhu, and J. Lloret, "Distributed parameter estimation for mobile wireless sensor network based on cloud computing in battlefield surveillance system", IEEE Access, vol. 3, pp. 1729-1739, 2015.
[http://dx.doi.org/10.1109/ACCESS.2015.2482981]
[8]
G. Ahmed, N.M. Khan, and M.M. Masood, "A dynamic transmission power control routing protocol to avoid network partitioning in wireless sensor networks", In: 2011 IEEE International Conference on Information and Communication Technologies (ICICT), 2011, pp. 1-4.
[http://dx.doi.org/10.1109/ICICT.2011.5983545]
[9]
L. Catarinucci, S. Guglielmi, R. Colella, and L. Tarricone, "Compact switched-beam antennas enabling novel power-efficient wireless sensor networks", IEEE Sens. J., vol. 14, no. 9, pp. 3252-3259, May 2014.
[http://dx.doi.org/10.1109/JSEN.2014.2326971]
[10]
N. Iliev, and I. Paprotny, "Review and comparison of spatial localization methods for low-power wireless sensor networks", IEEE Sens. J., vol. 15, no. 10, pp. 5971-5987, June 2015.
[http://dx.doi.org/10.1109/JSEN.2015.2450742]
[11]
H. Cotuk, K. Bicakci, B. Tavli, and E. Uzun, "The impact of transmission power control strategies on lifetime of wireless sensor networks", IEEE Trans. Comput., vol. 63, no. 11, pp. 2866-2879, July 2013.
[http://dx.doi.org/10.1109/TC.2013.151]
[12]
F.R. Yu, H. Tang, S. Bu, and D. Zheng, "Security and Quality of Service (QoS) co-design in cooperative mobile ad-hoc networks", EURASIP J. Wirel. Commun. Netw., vol. 2013, no. 1, pp. 1-14, Dec 2013.
[http://dx.doi.org/10.1186/1687-1499-2013-188]
[13]
Q. Guan, F.R. Yu, S. Jiang, and V. Leung, "Joint topology control and authentication design in mobile ad-hoc networks with cooperative communications", IEEE Trans. Vehicular Technol., vol. 61, no. 6, pp. 2674-2685, Apr 2012.
[http://dx.doi.org/10.1109/TVT.2012.2196061]
[14]
X. Liang, and Y. Xiao, "Game theory for network security", IEEE Comm. Surv. and Tutor., vol. 15, no. 1, pp. 472-486, July 2012.
[http://dx.doi.org/10.1109/SURV.2012.062612.00056]
[15]
R.B. Myerson, Game Theory., Harvard University Press, 2013.
[http://dx.doi.org/10.2307/j.ctvjsf522]
[16]
H.S. Bedi, S. Roy, and S. Shiva, "Game theory-based defense mechanisms against DDoS attacks on TCP/TCP-friendly flows", In: Proceeding IEEE Symposium on Computational Intelligence in Cyber Security (CICS), 2011, pp. 129-136.
[http://dx.doi.org/10.1109/CICYBS.2011.5949407]
[17]
M. Esmalifalak, G. Shi, Z. Han, and L. Song, "Bad data injection attack and defense in electricity market using game theory study", IEEE Trans. Smart Grid, vol. 4, no. 1, pp. 160-169, Jan 2013.
[http://dx.doi.org/10.1109/TSG.2012.2224391]
[18]
C. Liang, and K.R. Dandekar, "Power management in MIMO ad-hoc networks: A game-theoretic approach", IEEE Trans. Wirel. Commun., vol. 6, no. 4, pp. 1164-1170, Apr 2007.
[http://dx.doi.org/10.1109/TWC.2007.348307]
[19]
H. Zhang, O.P. Kreidl, B. DeCleene, J. Kurose, and X. Ni, "Security analysis of the bootstrap protocol for deny-by-default mobile ad-hoc networks", In: Proceeding IEEE Military Communications Conference (MILCOM), 2009, pp. 1-7.
[http://dx.doi.org/10.1109/MILCOM.2009.5379901]
[20]
S. Tan, and K. Kim, "Secure route discovery for preventing black hole attacks on AODV-based MANETs", In Proceeding IEEE International Conference on High Performance Computing and Communications and IEEE International Conference on Embedded and Ubiquitous Computing, 2013pp. 1159-1164
[http://dx.doi.org/10.1109/HPCC.and.EUC.2013.164]
[21]
S. Kurosawa, H. Nakayama, N. Kato, and A. Jamalipour, "Detecting blackhole attack on AODV-based mobile adhoc networks by dynamic learning method", Int. J. Netw. Secur., vol. 5, no. 3, pp. 338-346, Nov 2007.
[22]
P.N. Raj, and P.B. Swadas, "DPRAODV: A dynamic learning system against blackhole attack in AODV based MANET", Internat. J. Comput. Sci. Issu., vol. 2, pp. 54-59, Aug 2009.
[23]
Y. Wang, F.R. Yu, H. Tang, and M. Huang, "A mean field game theoretic approach for security enhancements in mobile ad-hoc networks", IEEE Trans. Wirel. Commun., vol. 13, no. 3, pp. 1616-1627, Jan 2014.
[http://dx.doi.org/10.1109/TWC.2013.122313.131118]
[24]
D. Djenouri, K. Lyes, and A.N. Badache, "A survey of security issues in mobile ad hoc and sensor networks", IEEE Comm. Surv. and Tutor., vol. 7, no. 4, pp. 2-28, Dec 2005.
[http://dx.doi.org/10.1109/COMST.2005.1593277]
[25]
X. Ge, H. Jia, Y. Zhong, Y. Xiao, Y. Li, and B. Vucetic, "Energy efficient optimization of wireless-powered 5G full duplex cellular networks: A mean field game approach", IEEE Trans. Green Commun. Netw., vol. 3, no. 2, pp. 455-467, Mar 2019.
[http://dx.doi.org/10.1109/TGCN.2019.2904093]
[26]
M.A. Abd, S.F. Al-Rubeaai, B.K. Singh, K.E. Tepe, and R. Benlamri, "Extending wireless sensor network lifetime with global energy balance", IEEE Sens. J., vol. 15, no. 9, pp. 5053-5063, May 2015.
[http://dx.doi.org/10.1109/JSEN.2015.2432114]
[27]
K. Bartos, and M. Rehak, "Self-organized mechanism for distributed setup of multiple heterogeneous intrusion detection systems", In: Proceedings IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems Workshops (SASOW), 2012, pp. 31-38.
[http://dx.doi.org/10.1109/SASOW.2012.15]
[28]
Q. Zhu, L. Bushnell, and T. Basar, "Game-theoretic analysis of node capture and cloning attack with multiple attackers in wireless sensor networks", In: Proceeding IEEE 51st Annual Conference on Decision and Control (CDC), 2012, pp. 3404-3411.
[http://dx.doi.org/10.1109/CDC.2012.6426481]
[29]
B.S. Jamin, M. Chatterjee, and T. Samanta, "Extensive game model for concurrent routing in wireless sensor network", In: Proceeding IEEE International Conference on Green Computing and Internet of Things (ICGCIoT), 2015, pp. 1156-1160.
[http://dx.doi.org/10.1109/ICGCIoT.2015.7380637]
[30]
A.Y. Al-Zahrani, F.R. Yu, and M. Huang, "A distributed interference control scheme in large cellular networks using mean-field game theory", In: Proceeding IEEE 24th International Symposium on Personal Indoor and Mobile Radio Communications (PIMRC), 2013, pp. 3339-3343.
[http://dx.doi.org/10.1109/PIMRC.2013.6666724]
[31]
A. Nayyar, and R. Singh, "Simulation and performance comparison of Ant Colony Optimization (ACO) routing protocol with AODV, DSDV, DSR routing protocols of wireless sensor networks using NS-2 simulator", Am. J. Intell. Syst., vol. 7, no. 1, pp. 19-30, July 2017.
[32]
A. Nayyar, and R. Singh, "A comprehensive review of simulation tools for wireless sensor networks (WSNs)", J. Wirel. Netw. Commun., vol. 5, no. 1, pp. 19-47, Jan 2015.
[33]
M. Kaur, and A. Nayyar, "A comprehensive review of mobile adhoc networks (MANETS)", Int. J. Emerg. Trends Technol. Comput. Sci., vol. 2, no. 6, pp. 196-210, Dec 2013.
[34]
D. Dhiman, and A. Nayyar, "Complete scenario of routing protocols, security leaks and attacks in MANETs", Int. J. Adv. Res. Comput. Sci. Softw. Eng., vol. 3, no. 10, pp. 1-12, Oct 2013.
[35]
A. Nayyar, "Enhanced anomaly detection IDS-based scheme for dynamic MANET On-demand (DYMO) routing protocol for MANETS", Int. J. Comput. Sci. Mobile Comput., vol. 2, no. 4, pp. 384-390, Apr 2013.
[36]
A. Nayyar, "Simulation based evaluation of reactive routing protocol for MANET", In: Proceeding IEEE Second International Conference on Advanced Computing and Communication Technology, 2012, pp. 561-568.
[http://dx.doi.org/10.1109/ACCT.2012.104]
[37]
A. Nayyar, "Cross-layer system for cluster based data access in MANET’S"Int. J. Comput. Sci. Inform., 2001, pp. 175-180.
[38]
T. Li, G. Kou, and Y. Peng, "Improving fraudulent URLs detection via feature engineering: Linear and nonlinear space transformation methods", Inf. Syst., vol. 91, p. 101494, July 2020.
[http://dx.doi.org/10.1016/j.is.2020.101494]
[39]
T. Li, Kou, Y. Peng, and Y. Shi, "Classifying with adaptive hyper-spheres: An incremental classifier based on competitive learning", IEEE Trans. Syst. Man Cybern. Syst., vol. 50, no. 4, pp. 1218-1229, Oct 2017.
[40]
G. Kou, P. Yang, Y. Peng, F. Xiao, Y. Chen, and F.E. Alsaadi, "Evaluation of feature selection methods for text classification with small datasets using multiple criteria decision-making methods", Appl. Soft Comput., vol. 86, p. 105836, Jan 2020.
[http://dx.doi.org/10.1016/j.asoc.2019.105836]
[41]
D. Nehra, K.S. Dhindsa, and B. Bhushan, "A security model to make communication secure in cluster-based MANETs", In: Advances in Intelligent Systems and Computing., Singapore: Springer Singapore, 2020, pp. 183-193.
[42]
V.V. Sarbhukan, and L. Ragha, "Establishing secure routing path using trust to enhance security in MANET", Wirel. Pers. Commun., vol. 110, no. 1, pp. 245-255, Jan 2020.
[http://dx.doi.org/10.1007/s11277-019-06724-0]
[43]
M.S. Hussain, and K.U. Khan, "A survey of IDS techniques in MANETs using machine-learning", In: Proceeding of the Third International Conference on Computational Intelligence and Informatics, 2020, pp. 743-751.
[http://dx.doi.org/10.1007/978-981-15-1480-7_68]

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