Name
Abstract | ||
|---|---|---|
The emanations of electronic and mechanical devices have raised serious privacy concerns. It proves possible for an attacker to recover the keystrokes by acoustic signal emanations. Most existing malicious applications adopt context-based approaches, which assume that the typed texts are potentially correlated. Those approaches often incur a high cost during the context learning stage, and can be limited by randomly typed contents (e.g., passwords). Also, context correlations can increase the risk of successive false recognition. We present a context-free and geometry-based approach to recover keystrokes. Using off-the-shelf smartphones to record acoustic emanations from keystrokes, this design estimates keystrokes' physical positions based on the Time Difference of Arrival (TDoA) method. We conduct extensive experiments and the results show that more than 72.2\\% of keystrokes can be successfully recovered. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2660267.2660296 | ACM Conference on Computer and Communications Security |
Keywords | Field | DocType |
acoustic emanations,context-free attack,keystroke recovery,unauthorized access | Internet privacy,Mechanical devices,Computer security,Computer science,Password,False recognition,Multilateration | Conference |
Citations | PageRank | References |
51 | 1.45 | 32 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tong Zhu | 1 | 89 | 5.60 |
| Qiang Ma | 2 | 167 | 14.03 |
| Shanfeng Zhang | 3 | 63 | 2.69 |
| Yunhao Liu | 4 | 8810 | 486.66 |