{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T12:42:12Z","timestamp":1785156132630,"version":"3.55.0"},"reference-count":29,"publisher":"Public Library of Science (PLoS)","issue":"12","license":[{"start":{"date-parts":[[2024,12,2]],"date-time":"2024-12-02T00:00:00Z","timestamp":1733097600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"2023 Guangxi Higher Education Undergraduate Teaching Reform Project: Teaching reform and innovation of Layout Design under the background of new liberal arts construction, general project A","award":["2023JGA355"],"award-info":[{"award-number":["2023JGA355"]}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>With the widespread application of monitoring technology and network storage technology, there are some privacy issues in the process of public service advertising visual design and the process of pushing public service advertising visual design works. Researching the privacy protection method of public service advertising visual design is of great significance to protecting the privacy data security of public service advertising visual designers and the personal privacy of other citizens. This paper proposes a digital watermark privacy protection method and a public service advertising visual design work push privacy protection method, and conducts a privacy protection experiment study on public service advertising visual design. The digital watermark privacy protection method and the public service advertising work push privacy protection method are used to provide an innovative solution for public service advertising privacy protection. The study shows that the evaluation score of the digital watermark privacy protection method is 11.05% higher than that of the traditional passive privacy protection method; the average feasibility evaluation score and the average effectiveness evaluation score of the privacy protection method for the public service advertising visual design work push by experts are 86.8 and 90.66 respectively. Combining the perspectives of artificial intelligence and the Internet of Things, this paper proposes a digital watermark privacy protection method, emphasizing practicality, and providing new ideas for privacy protection of public service advertising visual design.<\/jats:p>","DOI":"10.1371\/journal.pone.0308732","type":"journal-article","created":{"date-parts":[[2024,12,2]],"date-time":"2024-12-02T18:35:43Z","timestamp":1733164543000},"page":"e0308732","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":1,"title":["Evaluation of privacy protection methods of public service advertising visual design in the perspective of artificial intelligence internet of things"],"prefix":"10.1371","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-9584-1919","authenticated-orcid":true,"given":"Xujun","family":"Tang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2024,12,2]]},"reference":[{"issue":"8","key":"pone.0308732.ref001","first-page":"3628","article-title":"Location privacy protection based on differential privacy strategy for big data in industrial internet of things","volume":"14","author":"Yin Chunyong","year":"2017","journal-title":"IEEE Transactions on Industrial Informatics"},{"issue":"2","key":"pone.0308732.ref002","doi-asserted-by":"crossref","first-page":"2285","DOI":"10.1007\/s11042-016-4337-7","article-title":"Privacy protection vs. utility in visual data","volume":"77","author":"Thomas Winkler","year":"2018","journal-title":"Multimedia tools and applications"},{"issue":"29","key":"pone.0308732.ref003","first-page":"7928","article-title":"Privacy protection based on stream cipher for spatiotemporal data in IoT","volume":"7","author":"Tianen Liu","year":"2020","journal-title":"IEEE Internet of Things Journal"},{"issue":"4","key":"pone.0308732.ref004","first-page":"639","article-title":"Location data record privacy protection based on differential privacy mechanism","volume":"47","author":"Gu Ke","year":"2018","journal-title":"Information Technology and Control"},{"issue":"1","key":"pone.0308732.ref005","first-page":"12","article-title":"A Density-based Clustering Method for K-anonymity Privacy Protection","volume":"8","author":"Liu Jie","year":"2017","journal-title":"J. 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