Title: Generative AI and cybersecurity in 6G for intelligent English language learning systems
Authors: Lixia Xiang; Mei Wan; Ruobing Li; Cong Lin; Pan Zhang
Addresses: School of Foreign Language, Guangxi Science and Technology Normal University, 546199, China; Nanning University, Guangxi Nanning, 530299, China ' School of Foreign Language, Guangxi Science and Technology Normal University, 546199, China; Nanning University, Guangxi Nanning, 530299, China ' School of Foreign Language, Guangxi Science and Technology Normal University, 546199, China; Nanning University, Guangxi Nanning, 530299, China ' School of Foreign Language, Guangxi Science and Technology Normal University, 546199, China; Nanning University, Guangxi Nanning, 530299, China ' School of Foreign Language, Guangxi Science and Technology Normal University, 546199, China; Nanning University, Guangxi Nanning, 530299, China
Abstract: The convergence of generative artificial intelligence (AI) and sixth-generation (6G) communication technologies is changing how intelligent English language learning systems work. This paper presents learning with intelligible generative AI and 6G-based secure architecture (LINGUA-6G), a cohesive framework that amalgamates generative AI with ultra-low-latency, high-reliability 6G networks. Tests show that fluency improved by 28.7%, vocabulary retention by 32.4%, and latency by 41.2%. Network testing showed a response time of less than 90 ms, an availability rate of more than 96%, and stable performance. Blockchain identity verification and AI-based intrusion detection cut down on unauthorised access by 89.5% and found 96.8% of threats, proving that 6G-enabled AI learning ecosystems are safe, scalable, and efficient.
Keywords: generative artificial intelligence; 6G communication networks; intelligent language learning; blockchain-based identity verification; AI-driven intrusion detection.
DOI: 10.1504/IJICT.2026.154109
International Journal of Information and Communication Technology, 2026 Vol.27 No.63, pp.33 - 53
Received: 28 Jan 2026
Accepted: 05 Mar 2026
Published online: 12 Jun 2026 *


