Multiplayer reputation-based coalition game model (MRCGM) with dominant strategy analysis for detecting malicious attacks in wireless sensor networks

Gupta, Amara S A L G Gopala; Prasad, Gudapati Syam; Tumuluru, Praveen

doi:10.47974/JDMSC-1772

Open Access Research Article

Multiplayer reputation-based coalition game model (MRCGM) with dominant strategy analysis for detecting malicious attacks in wireless sensor networks

^*Amara S A L G Gopala GuptaCorresponding authoramara_gupta@yahoo.comDepartment of Computer Science and EngineeringKoneru Lakshmaiah Education FoundationVaddeswaram, AP, IndiaView full profile → , Gudapati Syam Prasadsyamprasad.gudapati@gmail.comDepartment of Computer Science and EngineeringSri Vasavi Institue of Engineering & TechnologyNandamuru, AP, IndiaView full profile → , Praveen Tumulurupraveenluru@gmail.comDepartment of Computer Science and EngineeringKoneru Lakshmaiah Education FoundationVaddeswaram, AP, IndiaView full profile →

* Corresponding author · click or hover a name for details

pp. 1473–1488Vol. 26Issue 5August 2023DOI: 10.47974/JDMSC-1772 Crossmark XML

Published Online:: 09 Sep 2023
Article type:: Research Article
Language:: EN
Article no.:: JDMSC-1772
Pages:: 1473–1488

Abstract

Wireless Sensor Networks (WSNs) are turning into an essential portion of our lives. Devoid of assuring WSNs security (WS), there remain no broad implementations of WSNs. Because of sensor nodes’ constrained capacities concerning computation, communication, and energy, giving protection to WSNs remains competitive. Indeed, the procedure of applying WS remains adaptable and vibrant that develops consistently. Attack-defend’s crux in WS could be conveyed by collaborative schemes of interdependency when Game Theory (GT) could be employed to consider communications amidst schemes of logical decision-makers. Hence, learning WS alongside GT possesses greater logic. This study proffers a Multiplayer Reputation-based Coalition Game Model (MRCGM) for seeking the false data injection amidst the nodes. An attacker attempts to sustain an ideal level of belief by correlating the identifications within the network (NW) to initiate a victorious transfer. Concurrently, the attacker should acquire a few charges for sustaining the trustability of its identifications. This proffered procedure employs this notion and turns the attack expensive by fixing a global threshold for nodes or identifications to be trustable and functional within the NW. Additionally, the beneficial function of the attacker and defender is as well described. The MRCGM has been correlated with 2 advanced methodologies like security-aware routing scheme employing repeated game (SARSRGM) paradigm and a Game-based Fuzzy Q-learning (GBFQL) scheme concerning diverse criteria. Consequently, the proffered MRCGM attains 124 kbps of Packet Drop Rate, 76.14% of energy efficiency, 96.1% of detection accuracy, 25.45% of energy consumption, and 102.45 ms of routing latency.

Keywords

Malicious identification Wireless sensor networks Game theory Reputation Coalitional model False data injection

Subject Classifications

68M18

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