{"title":"prnu泄漏:事实和补救措施","authors":"F. Pérez-González, Samuel Fernández-Menduiña","doi":"10.23919/Eusipco47968.2020.9287451","DOIUrl":null,"url":null,"abstract":"We address the problem of information leakage from estimates of the PhotoResponse Non-Uniformity (PRNU) fingerprints of a sensor. This leakage may compromise privacy in forensic scenarios, as it may reveal information from the images used in the PRNU estimation. We propose a new way to compute the information-theoretic leakage that is based on embedding synthetic PRNUs, and presesent affordable approximations and bounds. We also propose a new compact measure for the performance in membership inference tests. Finally, we analyze two potential countermeasures against leakage: binarization, which was already used in PRNU-storage contexts, and equalization, which is novel and offers better performance. Theoretical results are validated with experiments carried out on a real-world image dataset.","PeriodicalId":6705,"journal":{"name":"2020 28th European Signal Processing Conference (EUSIPCO)","volume":"34 1","pages":"720-724"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"PRNU-leaks: facts and remedies\",\"authors\":\"F. Pérez-González, Samuel Fernández-Menduiña\",\"doi\":\"10.23919/Eusipco47968.2020.9287451\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We address the problem of information leakage from estimates of the PhotoResponse Non-Uniformity (PRNU) fingerprints of a sensor. This leakage may compromise privacy in forensic scenarios, as it may reveal information from the images used in the PRNU estimation. We propose a new way to compute the information-theoretic leakage that is based on embedding synthetic PRNUs, and presesent affordable approximations and bounds. We also propose a new compact measure for the performance in membership inference tests. Finally, we analyze two potential countermeasures against leakage: binarization, which was already used in PRNU-storage contexts, and equalization, which is novel and offers better performance. Theoretical results are validated with experiments carried out on a real-world image dataset.\",\"PeriodicalId\":6705,\"journal\":{\"name\":\"2020 28th European Signal Processing Conference (EUSIPCO)\",\"volume\":\"34 1\",\"pages\":\"720-724\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 28th European Signal Processing Conference (EUSIPCO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/Eusipco47968.2020.9287451\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 28th European Signal Processing Conference (EUSIPCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/Eusipco47968.2020.9287451","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We address the problem of information leakage from estimates of the PhotoResponse Non-Uniformity (PRNU) fingerprints of a sensor. This leakage may compromise privacy in forensic scenarios, as it may reveal information from the images used in the PRNU estimation. We propose a new way to compute the information-theoretic leakage that is based on embedding synthetic PRNUs, and presesent affordable approximations and bounds. We also propose a new compact measure for the performance in membership inference tests. Finally, we analyze two potential countermeasures against leakage: binarization, which was already used in PRNU-storage contexts, and equalization, which is novel and offers better performance. Theoretical results are validated with experiments carried out on a real-world image dataset.