{"title":"数字取证:一种用于数字传感器识别的快速算法","authors":"J. Bernacki, R. Scherer","doi":"10.1080/24751839.2022.2058252","DOIUrl":null,"url":null,"abstract":"ABSTRACT We consider the identification of imaging devices by analysing images they produce. The problem is studied in the literature, yet the existing solutions are rather computationally demanding. We propose a high-speed algorithm for the identification of imaging devices. The aim is to provide additional security by identification of legitimate imaging devices or an identification for forensics. The experimental evaluation confirms efficient identification of devices models and brands by the proposed algorithm, compared with the state-of-the-art method. Moreover, our algorithm is approximately two orders of magnitude faster, which is very important in resource-constrained IoT ecosystems or very large databases.","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"6 1","pages":"399 - 419"},"PeriodicalIF":2.7000,"publicationDate":"2022-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Digital forensics: a fast algorithm for a digital sensor identification\",\"authors\":\"J. Bernacki, R. Scherer\",\"doi\":\"10.1080/24751839.2022.2058252\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT We consider the identification of imaging devices by analysing images they produce. The problem is studied in the literature, yet the existing solutions are rather computationally demanding. We propose a high-speed algorithm for the identification of imaging devices. The aim is to provide additional security by identification of legitimate imaging devices or an identification for forensics. The experimental evaluation confirms efficient identification of devices models and brands by the proposed algorithm, compared with the state-of-the-art method. Moreover, our algorithm is approximately two orders of magnitude faster, which is very important in resource-constrained IoT ecosystems or very large databases.\",\"PeriodicalId\":32180,\"journal\":{\"name\":\"Journal of Information and Telecommunication\",\"volume\":\"6 1\",\"pages\":\"399 - 419\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2022-04-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Information and Telecommunication\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/24751839.2022.2058252\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Information and Telecommunication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/24751839.2022.2058252","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Digital forensics: a fast algorithm for a digital sensor identification
ABSTRACT We consider the identification of imaging devices by analysing images they produce. The problem is studied in the literature, yet the existing solutions are rather computationally demanding. We propose a high-speed algorithm for the identification of imaging devices. The aim is to provide additional security by identification of legitimate imaging devices or an identification for forensics. The experimental evaluation confirms efficient identification of devices models and brands by the proposed algorithm, compared with the state-of-the-art method. Moreover, our algorithm is approximately two orders of magnitude faster, which is very important in resource-constrained IoT ecosystems or very large databases.