{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T14:31:34Z","timestamp":1779114694024,"version":"3.51.4"},"reference-count":0,"publisher":"Slovenian Association Informatika","issue":"13","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJCAI"],"abstract":"<jats:p>To solve the limitations of traditional database security detection, such as weak logical reasoning, delayed feature update, and high computational complexity under high-dimensional constraints, this study proposes a Bayesian optimization algorithm based on SAT. Security rules are formalized into CNF logical constraints, enabling automated reasoning and rule consistency verification via a satisfiability solver. A Gaussian process-driven Bayesian optimization framework with an improved Expected Improvement (EI) acquisition function dynamically updates feature weights and accelerates convergence toward high-risk regions, enhancing rare vulnerability detection and global solving efficiency. Experiments on enterprise database logs and national vulnerability datasets demonstrate an average detection rate of 97.5%, a defense success rate of 95.8%, and a response latency of 2.11 s, outperforming baseline methods. The system stability index reaches 0.93, with concurrent processing capability improved by 34.2%. These results confirm the algorithm\u2019s high-precision identification, stable defense performance, and practical deployability for database security management under complex, high-dimensional attack scenarios.<\/jats:p>","DOI":"10.31449\/inf.v50i13.13296","type":"journal-article","created":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T13:54:33Z","timestamp":1779112473000},"source":"Crossref","is-referenced-by-count":0,"title":["Bayesian Optimization with SAT Solver for Enhanced Database Security Identification"],"prefix":"10.31449","volume":"50","author":[{"given":"Huijuan","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"16141","published-online":{"date-parts":[[2026,5,18]]},"container-title":["Informatica"],"original-title":[],"link":[{"URL":"https:\/\/www.informatica.si\/index.php\/informatica\/article\/download\/13296\/6719","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.informatica.si\/index.php\/informatica\/article\/download\/13296\/6719","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T13:54:34Z","timestamp":1779112474000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.informatica.si\/index.php\/informatica\/article\/view\/13296"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,18]]},"references-count":0,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2026,5,18]]}},"URL":"https:\/\/doi.org\/10.31449\/inf.v50i13.13296","relation":{},"ISSN":["1854-3871","0350-5596"],"issn-type":[{"value":"1854-3871","type":"electronic"},{"value":"0350-5596","type":"print"}],"subject":[],"published":{"date-parts":[[2026,5,18]]}}}