{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,4]],"date-time":"2025-11-04T10:53:40Z","timestamp":1762253620331},"reference-count":0,"publisher":"World Scientific Pub Co Pte Lt","issue":"07n08","funder":[{"name":"State Grid Hebei Electric Power CO.LTD, China and the project of Research And Application of Network Security Vulnerability Mining Technology Based on Artificial Intelligence","award":["kj2019-062"],"award-info":[{"award-number":["kj2019-062"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Artif. Intell. Tools"],"published-print":{"date-parts":[[2020,12]]},"abstract":"<jats:p> In the information extraction, information sources can be screened according to the characteristics of the target network at the present stage, and the knowledge graph generated thereby can play a role in assisting the security analysis of the general network or power grid control network, mobile Internet and other special networks. In the method proposed in this paper, knowledge reasoning is mainly based on the attack conditions and attack methods to reason about the success rate and return of the attack. Through the obtained quality information, map construction information extraction and reasoning are performed to realize the correlation analysis of the information, and the information processing results are stored in the graphic structure. When analyzing the alerts generated by IDS, it is necessary to solve the multi-source alarm format generated by various devices produced by different suppliers. The attack diagram constructs the attack mode to guide the defense side to take targeted defense measures, and the attack success rate is used to judge the defense priority of all network nodes. After completing the construction of the graph, the attack graph is generated for the specific network environment under the guidance of the knowledge graph. In the process of attack graph generation, attack method and attack condition of attack instance can be used to guide the match of pre-condition and post-condition, so as to find the attack path. Attack success rate and attack profit attribute can be used to assist subsequent risk analysis. After simulation tests, the timeliness and availability of the system are verified, and this makes a contribution to the grid network management. <\/jats:p>","DOI":"10.1142\/s0218213020400242","type":"journal-article","created":{"date-parts":[[2020,11,30]],"date-time":"2020-11-30T04:24:36Z","timestamp":1606710276000},"page":"2040024","source":"Crossref","is-referenced-by-count":6,"title":["Research on Automatic Vulnerability Mining Model Based on Knowledge Graph"],"prefix":"10.1142","volume":"29","author":[{"given":"Ze","family":"Chen","sequence":"first","affiliation":[{"name":"State Grid Hebei Electric Power Research Institutes, Shijiazhuang, 50021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaojun","family":"Zuo","sequence":"additional","affiliation":[{"name":"State Grid Hebei Electric Power Research Institutes, Shijiazhuang, 50021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Botao","family":"Hou","sequence":"additional","affiliation":[{"name":"State Grid Hebei Electric Power Research Institutes, Shijiazhuang, 50021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Na","family":"Dong","sequence":"additional","affiliation":[{"name":"State Grid Hebei Electric Power Research Institutes, Shijiazhuang, 50021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Chang","sequence":"additional","affiliation":[{"name":"State Grid Hebei Electric Power Research Institutes, Shijiazhuang, 50021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2020,11,30]]},"container-title":["International Journal on Artificial Intelligence Tools"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218213020400242","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,11,30]],"date-time":"2020-11-30T04:24:39Z","timestamp":1606710279000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218213020400242"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,30]]},"references-count":0,"journal-issue":{"issue":"07n08","published-print":{"date-parts":[[2020,12]]}},"alternative-id":["10.1142\/S0218213020400242"],"URL":"https:\/\/doi.org\/10.1142\/s0218213020400242","relation":{},"ISSN":["0218-2130","1793-6349"],"issn-type":[{"value":"0218-2130","type":"print"},{"value":"1793-6349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,11,30]]}}}