{"title":"暗网取证:用数字取证追踪暗网活动的研究","authors":"R. Brinson, H. Wimmer, Lei Chen","doi":"10.1109/irtm54583.2022.9791646","DOIUrl":null,"url":null,"abstract":"The Dark Web has become home to malicious, illegal, and exploitative activities. Due to the nature of the Dark Web and the browsers used to reach it, uncovering these activities presents grave challenges to digital investigators or law enforcement agencies. In this work, we seek to use state of the art, closed-source Digital Forensics software to extract predefined Dark Web activities from a mobile device.","PeriodicalId":426354,"journal":{"name":"2022 Interdisciplinary Research in Technology and Management (IRTM)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Dark Web Forensics: An Investigation of Tracking Dark Web Activity with Digital Forensics\",\"authors\":\"R. Brinson, H. Wimmer, Lei Chen\",\"doi\":\"10.1109/irtm54583.2022.9791646\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Dark Web has become home to malicious, illegal, and exploitative activities. Due to the nature of the Dark Web and the browsers used to reach it, uncovering these activities presents grave challenges to digital investigators or law enforcement agencies. In this work, we seek to use state of the art, closed-source Digital Forensics software to extract predefined Dark Web activities from a mobile device.\",\"PeriodicalId\":426354,\"journal\":{\"name\":\"2022 Interdisciplinary Research in Technology and Management (IRTM)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-02-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 Interdisciplinary Research in Technology and Management (IRTM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/irtm54583.2022.9791646\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Interdisciplinary Research in Technology and Management (IRTM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/irtm54583.2022.9791646","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dark Web Forensics: An Investigation of Tracking Dark Web Activity with Digital Forensics
The Dark Web has become home to malicious, illegal, and exploitative activities. Due to the nature of the Dark Web and the browsers used to reach it, uncovering these activities presents grave challenges to digital investigators or law enforcement agencies. In this work, we seek to use state of the art, closed-source Digital Forensics software to extract predefined Dark Web activities from a mobile device.
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