Smartphone can spy on computer keyboard strikes

or more letters.

For example, take the word “canoe,” which, when typed breaks down into four keystroke pairs: “C-A, A-N, N-O and O-E.” Those pairs then translate into the detection system’s code as follows: Left-Left-Near, Left-Right-Far, Right-Right-Far and Right-Left-Far, or LLN-LRF-RRF-RLF. This code is then compared to the preloaded dictionary and yields “canoe” as the statistically probable typed word. Working with dictionaries comprising about 58,000 words, the system reached word-recovery rates as high as 80 percent.

“The way we see this attack working is that you, the phone’s owner, would request or be asked to download an innocuous-looking application, which doesn’t ask you for the use of any suspicious phone sensors,” said Henry Carter, a Ph.D. student in computer science and one of the study’s co-authors. “Then the keyboard-detection malware is turned on, and the next time you place your phone next to the keyboard and start typing, it starts listening.”

Mitigation strategies for this vulnerability are pretty simple and straightforward, Traynor said. First, since the study found an effective range of just three inches from a keyboard, phone users can simply leave their phones in their purses or pockets, or just move them further away from the keyboard. A fix that puts less onus on users, however, is to add a layer of security for phone accelerometers.

“The sampling rate for accelerometers is already pretty low, and if you cut it in half, you start to approach theoretical limitations that prevent eavesdropping. The malware simply does not have the data to work with,” Traynor said. “But most phone applications can still function even with that lower accelerometer rate. So manufacturers could set that as the default rate, and if someone downloads an application like a game that needs the higher sampling rate, that would prompt a permission question to the user to reset the accelerometer.”

In the meantime, Traynor said, users should not be paranoid that hackers are tracking their keystrokes through their iPhones.

“The likelihood of someone falling victim to an attack like this right now is pretty low,” he said. “This was really hard to do. But could people do it if they really wanted to? We think yes.”

The finding is reported in the paper, “(sp)iPhone: Decoding Vibrations From Nearby Keyboards Using Mobile Phone Accelerometers,” and will be presented Thursday, 20 October, at the 18th ACM Conference on Computer and Communications Security in Chicago. In addition to Carter, Traynor’s coauthors include Georgia Tech graduate student Arunabh Verman and Philip Marquardt of the MIT Lincoln Laboratory.