Yanchao Zhao, Yiming Zhao, Si Li, Hao Han, Linfu Xie
{"title":"UltraSnoop:通过基于智能手机的超声波声纳进行位置无关的击键窥探","authors":"Yanchao Zhao, Yiming Zhao, Si Li, Hao Han, Linfu Xie","doi":"10.1145/3614440","DOIUrl":null,"url":null,"abstract":"Keystroke snooping is an effective way to steal sensitive information from the victims. Recent research on acoustic emanation based techniques has greatly improved the accessibility by non-professional adversaries. However, these approaches either require multiple smartphones or require specific placement of the smartphone relative to the keyboards, which tremendously restrict the application scenarios. In this paper, we propose UltraSnoop, a training-free, transferable, and placement-agnostic scheme, which manages to infer user’s input using a single smartphone placed within the range covered by a microphone and speaker. The innovation of Ultrasnoop is that we propose an ultrasonic anchor-keystroke positioning method and an MFCCs clustering algorithm, synthesis of which could infer the relative position between the smartphone and the keyboard. Along with the keystroke TDoA, our method could infer the keystrokes and even gradually improve the accuracy as the snooping proceeds. Our real-world experiments show that UltraSnoop could achieve more than 85% top-3 snooping accuracy when the smartphone is placed within the range of 30-60cm from the keyboard.","PeriodicalId":29764,"journal":{"name":"ACM Transactions on Internet of Things","volume":"33 1","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"UltraSnoop: Placement-agnostic Keystroke Snooping via Smartphone-based Ultrasonic Sonar\",\"authors\":\"Yanchao Zhao, Yiming Zhao, Si Li, Hao Han, Linfu Xie\",\"doi\":\"10.1145/3614440\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Keystroke snooping is an effective way to steal sensitive information from the victims. Recent research on acoustic emanation based techniques has greatly improved the accessibility by non-professional adversaries. However, these approaches either require multiple smartphones or require specific placement of the smartphone relative to the keyboards, which tremendously restrict the application scenarios. In this paper, we propose UltraSnoop, a training-free, transferable, and placement-agnostic scheme, which manages to infer user’s input using a single smartphone placed within the range covered by a microphone and speaker. The innovation of Ultrasnoop is that we propose an ultrasonic anchor-keystroke positioning method and an MFCCs clustering algorithm, synthesis of which could infer the relative position between the smartphone and the keyboard. Along with the keystroke TDoA, our method could infer the keystrokes and even gradually improve the accuracy as the snooping proceeds. Our real-world experiments show that UltraSnoop could achieve more than 85% top-3 snooping accuracy when the smartphone is placed within the range of 30-60cm from the keyboard.\",\"PeriodicalId\":29764,\"journal\":{\"name\":\"ACM Transactions on Internet of Things\",\"volume\":\"33 1\",\"pages\":\"\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2023-08-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Transactions on Internet of Things\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3614440\",\"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":"ACM Transactions on Internet of Things","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3614440","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
UltraSnoop: Placement-agnostic Keystroke Snooping via Smartphone-based Ultrasonic Sonar
Keystroke snooping is an effective way to steal sensitive information from the victims. Recent research on acoustic emanation based techniques has greatly improved the accessibility by non-professional adversaries. However, these approaches either require multiple smartphones or require specific placement of the smartphone relative to the keyboards, which tremendously restrict the application scenarios. In this paper, we propose UltraSnoop, a training-free, transferable, and placement-agnostic scheme, which manages to infer user’s input using a single smartphone placed within the range covered by a microphone and speaker. The innovation of Ultrasnoop is that we propose an ultrasonic anchor-keystroke positioning method and an MFCCs clustering algorithm, synthesis of which could infer the relative position between the smartphone and the keyboard. Along with the keystroke TDoA, our method could infer the keystrokes and even gradually improve the accuracy as the snooping proceeds. Our real-world experiments show that UltraSnoop could achieve more than 85% top-3 snooping accuracy when the smartphone is placed within the range of 30-60cm from the keyboard.