{"title":"Forensic identification of GSM mobile phones","authors":"Jakob Hasse, Thomas Gloe, Martin Beck","doi":"10.1145/2482513.2482529","DOIUrl":null,"url":null,"abstract":"With the rapid growth of GSM telecommunication, special requirements arise in digital forensics to identify mobile phones operating in a GSM network. This paper introduces a novel method to identify GSM devices based on physical characteristics of the radio frequency hardware. An implementation of a specialised receiver software allows passive monitoring of GSM traffic along with physical layer burst extraction even for handover and frequency hopping techniques. We introduce time-based patterns of modulation errors as a unique device-dependent feature and carefully remove random effects of the wireless communication channel. Using our characteristics, we could distinguish 13 mobile phones at an overall success rate of 97.62% under real-world conditions. This work proves practical feasibility of physical layer identification scenarios capable of tracking or authenticating GSM-based devices.","PeriodicalId":243756,"journal":{"name":"Information Hiding and Multimedia Security Workshop","volume":"160 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Hiding and Multimedia Security Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2482513.2482529","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 29
Abstract
With the rapid growth of GSM telecommunication, special requirements arise in digital forensics to identify mobile phones operating in a GSM network. This paper introduces a novel method to identify GSM devices based on physical characteristics of the radio frequency hardware. An implementation of a specialised receiver software allows passive monitoring of GSM traffic along with physical layer burst extraction even for handover and frequency hopping techniques. We introduce time-based patterns of modulation errors as a unique device-dependent feature and carefully remove random effects of the wireless communication channel. Using our characteristics, we could distinguish 13 mobile phones at an overall success rate of 97.62% under real-world conditions. This work proves practical feasibility of physical layer identification scenarios capable of tracking or authenticating GSM-based devices.