Advanced Drone Swarm Security by Using Blockchain Governance Game

Song-Kyoo (Amang) Kim ()
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Song-Kyoo (Amang) Kim: Faculty of Applied Sciences, Macao Polytechnic University, R. de Luis Gonzaga Gomes, Macao SAR, China

Mathematics, 2022, vol. 10, issue 18, 1-13

Abstract: This research contributes to the security design of an advanced smart drone swarm network based on a variant of the Blockchain Governance Game (BGG), which is the theoretical game model to predict the moments of security actions before attacks, and the Strategic Alliance for Blockchain Governance Game (SABGG), which is one of the BGG variants which has been adapted to construct the best strategies to take preliminary actions based on strategic alliance for protecting smart drones in a blockchain-based swarm network. Smart drones are artificial intelligence (AI)-enabled drones which are capable of being operated autonomously without having any command center. Analytically tractable solutions from the SABGG allow us to estimate the moments of taking preliminary actions by delivering the optimal accountability of drones for preventing attacks. This advanced secured swarm network within AI-enabled drones is designed by adapting the SABGG model. This research helps users to develop a new network-architecture-level security of a smart drone swarm which is based on a decentralized network.

Keywords: drone swarm; cybersecurity; Blockchain Governance Game; strategic alliance; artificial intelligence; network architecture; Internet of Things; fluctuation theory; 51 percent attack (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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