{"title":"基于隐私保护的MFS加密图像特征提取","authors":"Guoming Chen, Qiang Chen, Xiongyong Zhu, Yiqun Chen","doi":"10.1109/ICDH.2018.00016","DOIUrl":null,"url":null,"abstract":"Privacy preserve machine learning is a hot topic in multimedia domain. In this paper, we propose a secure multifractal feature extraction and representation method in the encrypted domain. We first use chaotic sequence to scramble the image in a block wise way, then according to the characteristic of chaotic sequence which preserves locally the randomness and maintain special periodicity we propose a multifractal feature extraction method in the encrypted domain. Experimental results showed that multifractal feature has a good distinguish ability in the encrypted domain.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Encrypted Image Feature Extraction by Privacy-Preserving MFS\",\"authors\":\"Guoming Chen, Qiang Chen, Xiongyong Zhu, Yiqun Chen\",\"doi\":\"10.1109/ICDH.2018.00016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Privacy preserve machine learning is a hot topic in multimedia domain. In this paper, we propose a secure multifractal feature extraction and representation method in the encrypted domain. We first use chaotic sequence to scramble the image in a block wise way, then according to the characteristic of chaotic sequence which preserves locally the randomness and maintain special periodicity we propose a multifractal feature extraction method in the encrypted domain. Experimental results showed that multifractal feature has a good distinguish ability in the encrypted domain.\",\"PeriodicalId\":117854,\"journal\":{\"name\":\"2018 7th International Conference on Digital Home (ICDH)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 7th International Conference on Digital Home (ICDH)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDH.2018.00016\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 7th International Conference on Digital Home (ICDH)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDH.2018.00016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Encrypted Image Feature Extraction by Privacy-Preserving MFS
Privacy preserve machine learning is a hot topic in multimedia domain. In this paper, we propose a secure multifractal feature extraction and representation method in the encrypted domain. We first use chaotic sequence to scramble the image in a block wise way, then according to the characteristic of chaotic sequence which preserves locally the randomness and maintain special periodicity we propose a multifractal feature extraction method in the encrypted domain. Experimental results showed that multifractal feature has a good distinguish ability in the encrypted domain.