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Then, this paper proposes a new method called dynamic giant connected component (GCC)-based scale-intensity centrality (DGSIC) that combines the local, global, and community structure of DCPN to identify critical nodes with stronger communication capabilities. The dynamic strategy involves the iterative identification of one critical node at each step, considering the evolving network configuration and ensuring the identified node remains the most critical in the present network. Additionally, the prioritization strategy is employed to identify the nodes within the GCC, which can significantly impact the network connectivity and communication. DGSIC optimizes the attack sequence for directed energy attacks, facilitating the rapid dissolution of malicious drone swarms. Extensive experiments in four simulated networks and eight real-world networks demonstrate the superior robustness and cascading failure performance of DGSIC.<\/jats:p>","DOI":"10.1007\/s40747-023-01316-9","type":"journal-article","created":{"date-parts":[[2024,1,17]],"date-time":"2024-01-17T06:01:56Z","timestamp":1705471316000},"page":"3197-3211","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["A communication-based identification of critical drones in malicious drone swarm networks"],"prefix":"10.1007","volume":"10","author":[{"given":"Min","family":"Teng","sequence":"first","affiliation":[]},{"given":"Chao","family":"Gao","sequence":"additional","affiliation":[]},{"given":"Zhen","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Xuelong","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,1,17]]},"reference":[{"key":"1316_CR1","doi-asserted-by":"crossref","first-page":"1633","DOI":"10.1007\/s40747-021-00300-5","volume":"7","author":"Y Wu","year":"2021","unstructured":"Wu Y, Wu S, Hu X (2021) Multi-constrained cooperative path planning of multiple drones for persistent surveillance in urban environments. 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