{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T21:44:19Z","timestamp":1764020659690,"version":"3.38.0"},"reference-count":20,"publisher":"SAGE Publications","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JHS"],"published-print":{"date-parts":[[2023,11,14]]},"abstract":"<jats:p>Instantaneous traffic changes in high-speed networks will interfere with abnormal traffic characteristics, making it difficult to accurately identify hidden targets of security threats. This paper designs a high-speed network security threat hidden target recognition method based on attack graph theory. Using the high-speed network traffic reduction method, under the condition that the network topology remains unchanged, the instantaneous input traffic is reduced according to a certain proportion, and after compressing the flow data scale, the abnormal traffic of the high-speed network is identified through the convolutional recurrent neural network, and the information entropy is used to describe the high-speed network. The abnormal traffic characteristics of the network are used as constraints to design an attack graph of hidden targets of high-speed network security threats, and an attack path discovery method based on multi-heuristic information fusion is designed to extract attack paths of high-speed networks, locate attacking hosts, and identify hidden threat targets. In the experiment, the method can accurately identify the hidden targets of high-speed network security threats, and has better identification ability.<\/jats:p>","DOI":"10.3233\/jhs-222048","type":"journal-article","created":{"date-parts":[[2023,5,19]],"date-time":"2023-05-19T16:25:55Z","timestamp":1684513555000},"page":"307-320","source":"Crossref","is-referenced-by-count":1,"title":["Hidden target recognition method for high-speed network security threats based on attack graph theory"],"prefix":"10.1177","volume":"29","author":[{"given":"Limin","family":"Song","sequence":"first","affiliation":[{"name":"School of Electronics & Information Engineering, Zhengzhou Sias University, Zhengzhou, China"}]},{"given":"Seungmin","family":"Rho","sequence":"additional","affiliation":[{"name":"Department of Industrial Security, Chung-Ang University, Seoul, 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