Abstract
Mobile phones nowadays are equipped with at least dual microphones. We find when a user is typing on a phone, the sounds generated from the vibration caused by finger's tapping on the screen surface can be captured by both microphones, and these recorded sounds alone are informative enough to infer the user's keystrokes. This ability can be leveraged to enable useful application designs, while it also raises a crucial privacy risk that the private information typed by users on mobile phones has a great potential to be leaked through such a recognition ability. In this paper, we address two key design issues and demonstrate, more importantly alarm people, that this risk is possible, which could be related to many of us when we use our mobile phones. We implement our proposed techniques in a prototype system and conduct extensive experiments. The evaluation results indicate promising successful rates for more than 4000 keystrokes from different users on various types of mobile phones.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2020 IEEE 40th International Conference on Distributed Computing Systems (ICDCS 2020) |
| Publisher | IEEE |
| Pages | 965-975 |
| ISBN (Electronic) | 978-1-7281-7002-2 |
| DOIs | |
| Publication status | Published - Nov 2020 |
| Event | 40th IEEE International Conference on Distributed Computing Systems (ICDCS 2020) - Virtual, Singapore Duration: 29 Nov 2020 → 1 Dec 2020 Conference number: 40 https://icdcs2020.sg/ |
Publication series
| Name | Proceedings - International Conference on Distributed Computing Systems |
|---|---|
| Volume | 2020-November |
Conference
| Conference | 40th IEEE International Conference on Distributed Computing Systems (ICDCS 2020) |
|---|---|
| Abbreviated title | ICDCS'20 |
| Place | Singapore |
| Period | 29/11/20 → 1/12/20 |
| Internet address |
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