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The results have been compared with existing approaches. The experimental results show an improvement in the proposed noise-based privacy-preserving model in terms of computational overhead. The comparative analysis indicates that the proposed model without the fuzzifier has around 52\u201377% less computational overhead than the Data access control scheme and 46\u201370% less computational overhead compared to the Dynamic Privacy Protection model. The proposed model with the fuzzifier has around 48\u201373% less computational overhead compared to the Data access control scheme and 31\u201363% less computational overhead compared to the Dynamic Privacy Protection model. Furthermore, the privacy analysis has been done with the relevant approaches. The results indicate that the proposed model can customize privacy as per the users\u2019 preferences and at the same time takes less execution time which reduces the overhead on the resource constraint IoT devices.<\/jats:p>","DOI":"10.1007\/s40747-021-00489-5","type":"journal-article","created":{"date-parts":[[2021,8,25]],"date-time":"2021-08-25T09:03:39Z","timestamp":1629882219000},"page":"3655-3679","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["A noise-based privacy preserving model for Internet of Things"],"prefix":"10.1007","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9692-9505","authenticated-orcid":false,"given":"Shelendra Kumar","family":"Jain","sequence":"first","affiliation":[]},{"given":"Nishtha","family":"Kesswani","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,8,25]]},"reference":[{"key":"489_CR1","doi-asserted-by":"crossref","unstructured":"Solanki A, Nayyar A (2019) Green internet of things (g-IoT): Ict technologies, principles, applications, projects, and challenges. 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