Nam In Park , Ji Woo Lee , Seong Ho Lim , Oc-Yueb Jeon , Jin-Hwan Kim , Jun Seok Byun , Chanjun Chun , Jung-Hwan Lee
{"title":"验证基于 Tizen 的三星 Galaxy 手表音频文件的先进取证方法","authors":"Nam In Park , Ji Woo Lee , Seong Ho Lim , Oc-Yueb Jeon , Jin-Hwan Kim , Jun Seok Byun , Chanjun Chun , Jung-Hwan Lee","doi":"10.1016/j.fsidi.2024.301697","DOIUrl":null,"url":null,"abstract":"<div><p>In this study, we propose a forensic-forgery detecting approach for audio files, an extension of previous research on the Android-based Samsung Galaxy Watch4 series, captured by the Voice Recorder application on Samsung Galaxy smartwatches with the Tizen operating system (OS). We collected 200 audio files from five different Galaxy Watch models equipped with the Tizen OS and paired them with smartphones using Bluetooth. We analyzed the specific features of the audio files captured by smartwatches, such as audio latency, audio tailing, timestamps, and file structure, and examined the specific features between audio files captured in the smartwatches and those manipulated by the recording application installed by default in the paired smartphones. Furthermore, audio files from smartwatches can be analyzed using the Smart Development Bridge (SDB) tool and it compares the timestamps from smartwatch audio files with those in the file system. The experiments revealed that the audio latency/tailing, attributes, and file structure of audio files captured by smartwatches differed from those of smartphones with the Tizen OS. Additionally, by examining the audio latency/tailing and attributes of the file structure, we detected if the audio files were manipulated, and track and classify where the audio files were manipulated. Finally, the audio files captured in the Samsung Galaxy Watches with the Tizen OS can be authenticated forensically by comparing the timestamps of the audio files in the smartwatch file system and those stored in the audio files. We believe our findings may be useful for audio-related digital forensics.</p></div>","PeriodicalId":48481,"journal":{"name":"Forensic Science International-Digital Investigation","volume":"48 ","pages":"Article 301697"},"PeriodicalIF":2.0000,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666281724000064/pdfft?md5=e1795316b3d740ff97ed68e1612ff0ed&pid=1-s2.0-S2666281724000064-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Advanced forensic method to authenticate audio files from Tizen-based Samsung Galaxy Watches\",\"authors\":\"Nam In Park , Ji Woo Lee , Seong Ho Lim , Oc-Yueb Jeon , Jin-Hwan Kim , Jun Seok Byun , Chanjun Chun , Jung-Hwan Lee\",\"doi\":\"10.1016/j.fsidi.2024.301697\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In this study, we propose a forensic-forgery detecting approach for audio files, an extension of previous research on the Android-based Samsung Galaxy Watch4 series, captured by the Voice Recorder application on Samsung Galaxy smartwatches with the Tizen operating system (OS). We collected 200 audio files from five different Galaxy Watch models equipped with the Tizen OS and paired them with smartphones using Bluetooth. We analyzed the specific features of the audio files captured by smartwatches, such as audio latency, audio tailing, timestamps, and file structure, and examined the specific features between audio files captured in the smartwatches and those manipulated by the recording application installed by default in the paired smartphones. Furthermore, audio files from smartwatches can be analyzed using the Smart Development Bridge (SDB) tool and it compares the timestamps from smartwatch audio files with those in the file system. The experiments revealed that the audio latency/tailing, attributes, and file structure of audio files captured by smartwatches differed from those of smartphones with the Tizen OS. Additionally, by examining the audio latency/tailing and attributes of the file structure, we detected if the audio files were manipulated, and track and classify where the audio files were manipulated. Finally, the audio files captured in the Samsung Galaxy Watches with the Tizen OS can be authenticated forensically by comparing the timestamps of the audio files in the smartwatch file system and those stored in the audio files. We believe our findings may be useful for audio-related digital forensics.</p></div>\",\"PeriodicalId\":48481,\"journal\":{\"name\":\"Forensic Science International-Digital Investigation\",\"volume\":\"48 \",\"pages\":\"Article 301697\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2024-02-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2666281724000064/pdfft?md5=e1795316b3d740ff97ed68e1612ff0ed&pid=1-s2.0-S2666281724000064-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Forensic Science International-Digital Investigation\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666281724000064\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Forensic Science International-Digital Investigation","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666281724000064","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Advanced forensic method to authenticate audio files from Tizen-based Samsung Galaxy Watches
In this study, we propose a forensic-forgery detecting approach for audio files, an extension of previous research on the Android-based Samsung Galaxy Watch4 series, captured by the Voice Recorder application on Samsung Galaxy smartwatches with the Tizen operating system (OS). We collected 200 audio files from five different Galaxy Watch models equipped with the Tizen OS and paired them with smartphones using Bluetooth. We analyzed the specific features of the audio files captured by smartwatches, such as audio latency, audio tailing, timestamps, and file structure, and examined the specific features between audio files captured in the smartwatches and those manipulated by the recording application installed by default in the paired smartphones. Furthermore, audio files from smartwatches can be analyzed using the Smart Development Bridge (SDB) tool and it compares the timestamps from smartwatch audio files with those in the file system. The experiments revealed that the audio latency/tailing, attributes, and file structure of audio files captured by smartwatches differed from those of smartphones with the Tizen OS. Additionally, by examining the audio latency/tailing and attributes of the file structure, we detected if the audio files were manipulated, and track and classify where the audio files were manipulated. Finally, the audio files captured in the Samsung Galaxy Watches with the Tizen OS can be authenticated forensically by comparing the timestamps of the audio files in the smartwatch file system and those stored in the audio files. We believe our findings may be useful for audio-related digital forensics.