Wybren van der Meer, Kim-Kwang Raymond Choo, Nhien-An Le-Khac, Mohand Tahar Kechadi
{"title":"Investigation and Automating Extraction of Thumbnails Produced by Image Viewers","authors":"Wybren van der Meer, Kim-Kwang Raymond Choo, Nhien-An Le-Khac, Mohand Tahar Kechadi","doi":"10.1109/Trustcom/BigDataSE/ICESS.2017.355","DOIUrl":null,"url":null,"abstract":"Data carving is generally used to recover deleted images in digital investigations, but carving time can be significant and the deleted images may have been overwritten. Thus, thumbnails of (deleted) images are an alternative evidence, and can often be found within databases created by either operating systems or image viewers. Existing literature generally focus on the extraction of thumbnails from databases created by the operating system. Understanding thumbnails created by image reviewers is relatively understudied. Therefore, in this paper, we propose a new approach of automating extraction of thumbnails produced by image viewers. We then evaluate the utility of our approach using popular image viewers.","PeriodicalId":170253,"journal":{"name":"2017 IEEE Trustcom/BigDataSE/ICESS","volume":"2009 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Trustcom/BigDataSE/ICESS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/Trustcom/BigDataSE/ICESS.2017.355","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Data carving is generally used to recover deleted images in digital investigations, but carving time can be significant and the deleted images may have been overwritten. Thus, thumbnails of (deleted) images are an alternative evidence, and can often be found within databases created by either operating systems or image viewers. Existing literature generally focus on the extraction of thumbnails from databases created by the operating system. Understanding thumbnails created by image reviewers is relatively understudied. Therefore, in this paper, we propose a new approach of automating extraction of thumbnails produced by image viewers. We then evaluate the utility of our approach using popular image viewers.