Cybersecurity entity recognition model for IoT via hierarchical attention mechanism

Chunwang Wu, Jiayong Liu, Cheng Huang and Linxia Li
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Chunwang Wu: School of Cyber Science and Engineering, Sichuan University, Chengdu, P. R. China†Advanced Cryptography and System Security Key Laboratory of Sichuan Province, Chengdu, P. R. China
Jiayong Liu: School of Cyber Science and Engineering, Sichuan University, Chengdu, P. R. China
Cheng Huang: School of Cyber Science and Engineering, Sichuan University, Chengdu, P. R. China
Linxia Li: ��School of Preclinical Medicine, Chengdu University, Chengdu, P. R. China

International Journal of Modern Physics C (IJMPC), 2025, vol. 36, issue 10, 1-15

Abstract: In the current landscape, the Internet of Things (IoT) finds its utility across diverse sectors, including finance, healthcare, and beyond. However, security emerges as the principal obstacle impeding the advancement of IoT. Given the intricate nature of IoT cybersecurity, traditional security protocols fall short when addressing the unique challenges within the IoT domain. Security strategies anchored in the cybersecurity knowledge graph present a robust solution to safeguard IoT ecosystems. The foundation of these strategies lies in the intricate networks of the cybersecurity knowledge graph, with Named Entity Recognition (NER) serving as a crucial initial step in its implementation. Conventional cybersecurity entity recognition approaches IoT grapple with the complexity of cybersecurity entities, characterized by their sophisticated structures and vague meanings. Additionally, these traditional models are inadequate at discerning all the interrelations between cybersecurity entities, rendering their direct application in IoT security impractical. This paper introduces an innovative Cybersecurity Entity Recognition Model, referred to as CERM, designed to pinpoint cybersecurity entities within IoT. CERM employs a hierarchical attention mechanism that proficiently maps the interdependencies among cybersecurity entities. Leveraging these mapped dependencies, CERM precisely identifies IoT cybersecurity entities. Comparative evaluation experiments illustrate CERM’s superior performance over the existing entity recognition models, marking a significant advancement in the field of IoT security.

Keywords: Cybersecurity; named entity recognition; complex network; knowledge graph; hierarchical attention mechanism (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1142/S0129183124420130

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