{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,21]],"date-time":"2025-06-21T10:10:08Z","timestamp":1750500608055,"version":"3.41.0"},"reference-count":15,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,6,21]],"date-time":"2025-06-21T00:00:00Z","timestamp":1750464000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,6,21]],"date-time":"2025-06-21T00:00:00Z","timestamp":1750464000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"The study was supported by Yunnan Power Grid Co., LTD. Technology project \u201c smart grid equipment firmware vulnerability detection technology \u201d","award":["No: YNKJXM20220088","No: YNKJXM20220088","No: YNKJXM20220088","No: YNKJXM20220088"],"award-info":[{"award-number":["No: YNKJXM20220088","No: YNKJXM20220088","No: YNKJXM20220088","No: YNKJXM20220088"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Discov Artif Intell"],"DOI":"10.1007\/s44163-025-00347-0","type":"journal-article","created":{"date-parts":[[2025,6,21]],"date-time":"2025-06-21T09:47:36Z","timestamp":1750499256000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Static detection method for multi-level network source code vulnerabilities based on knowledge graph technology"],"prefix":"10.1007","volume":"5","author":[{"given":"Peng","family":"Xiao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lina","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying","family":"Yan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenhong","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,6,21]]},"reference":[{"key":"347_CR1","doi-asserted-by":"crossref","unstructured":"Qasem A, Shirani P, Debbabi M, Wang L, Lebel B, Agba BL. Automatic vulnerability detection in embedded devices and firmware: survey and layered taxonomies. ACM Comput Surveys. 2022;54(2):25.1\u201342.","DOI":"10.1145\/3432893"},{"key":"347_CR2","unstructured":"Ma Q, Wu Z, Wang Y, Wang X. Approach of web application access control vulnerability detection based on state deviation analysis. Comput Sci. 2023;50(02):346\u201352."},{"key":"347_CR3","doi-asserted-by":"crossref","unstructured":"Senanayake J, Kalutarage H, Al-Kadri APL. Android source code vulnerability detection: a systematic literature review. ACM Comput Surv. 2023;55(9):1.1\u201337.","DOI":"10.1145\/3556974"},{"key":"347_CR4","doi-asserted-by":"crossref","unstructured":"Jain VK, Tripathi M. An integrated deep learning model for Ethereum smart contract vulnerability detection. Int J Inf Secur. 2024;23(1):557\u201375.","DOI":"10.1007\/s10207-023-00752-5"},{"key":"347_CR5","unstructured":"Yang H, Yang H, Zhang L, Cheng X. Feature dependence graph based source code loophole detection method. J Commun. 2023;44(01):103\u2013117."},{"key":"347_CR6","unstructured":"Wen M, Wang R, Jiang S. Source code vulnerability detection based on relational graph convolution network. J Comput Appl. 2022;42(06):1814\u201321."},{"key":"347_CR7","doi-asserted-by":"crossref","unstructured":"Ehrenberg M, Sarkani S, Mazzuchi TA. Python source code vulnerability detection with named entity recognition. Comput Secur. 2024;140:103802.1\u2013103802.15.","DOI":"10.1016\/j.cose.2024.103802"},{"key":"347_CR8","doi-asserted-by":"crossref","unstructured":"Bhandari GP, Assres G, Gavric N, Shalaginov A, Grnli TM. IoTvulCode: AI-enabled vulnerability detection in software products designed for IoT applications. Int J Inf Secur. 2024;23(4):2677\u201390.","DOI":"10.1007\/s10207-024-00848-6"},{"key":"347_CR9","unstructured":"He J, Cai R, Yin X, Lu X, Liu S. Detection of web command injection vulnerability for Cisco IOS-XE. Comput Sci. 2023;50(04):343\u201350."},{"key":"347_CR10","doi-asserted-by":"crossref","unstructured":"Toprak A, Turan M. Enhanced named entity recognition algorithm for financial document verification. J Supercomput. 2023;79(17):19431\u201351.","DOI":"10.1007\/s11227-023-05371-4"},{"key":"347_CR11","unstructured":"Lu Q, Yuan L. Software named entity recognition simulation based on combined neural network. Comput Simul. 2023;40(01):489\u2013492+509."},{"key":"347_CR12","doi-asserted-by":"crossref","unstructured":"Ahin CB. Semantic-based vulnerability detection by functional connectivity of gated graph sequence neural networks. Soft Comput. 2023;27(9):5703\u201319.","DOI":"10.1007\/s00500-022-07777-3"},{"key":"347_CR13","doi-asserted-by":"crossref","unstructured":"Pise RG, Patil S. Pioneering automated vulnerability detection for smart contracts in blockchain using KEVM: Guardian ADRGAN. Int J Inf Secur. 2024;23(3):1805\u201319.","DOI":"10.1007\/s10207-024-00817-z"},{"key":"347_CR14","doi-asserted-by":"crossref","unstructured":"Porkodi S, Kesavaraja D. Smart contract: a survey towards extortionate vulnerability detection and security enhancement. Wirel Netw. 2024;30(3):1285\u2013304.","DOI":"10.1007\/s11276-023-03587-z"},{"key":"347_CR15","unstructured":"Zhao M, Li D. A method of software source code vulnerability detection based on BGRU. Mod Electron Techn. 2022;45(18):57\u201362."}],"container-title":["Discover Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44163-025-00347-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s44163-025-00347-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44163-025-00347-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,21]],"date-time":"2025-06-21T09:47:40Z","timestamp":1750499260000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s44163-025-00347-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,21]]},"references-count":15,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["347"],"URL":"https:\/\/doi.org\/10.1007\/s44163-025-00347-0","relation":{},"ISSN":["2731-0809"],"issn-type":[{"value":"2731-0809","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,21]]},"assertion":[{"value":"29 November 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 May 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 June 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and Consent to Participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interest"}},{"value":"The raw data can be obtained on request from the corresponding author.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Data availability"}}],"article-number":"120"}}