Don't get paranoid, but a Georgia Tech research team says it's possible to use a phone to track what a person's typing on their keyboard nearby.
They say hackers could use a smartphone accelerometer to sense keyboard vibrations and decipher complete sentences with up to 80 percent accuracy.
"We first tried our experiments with an iPhone 3GS, and the results were difficult to read," says assistant professor Patrick Traynor.
"But then we tried an iPhone 4, which has an added gyroscope to clean up the accelerometer noise, and the results were much better. We believe that most smartphones made in the past two years are sophisticated enough to launch this attack."
The technique works through probability and by detecting pairs of keystrokes, rather than individual keys. It models 'keyboard events' in pairs, then determines whether the pair of keys pressed is on the left or the right side of the keyboard, and whether they're close together or far apart.
It then compares the results against a preloaded dictionary, each word of which has been broken down by similar measurements. The technique only works reliably on words of three or more letters.
For example, the word 'canoe' breaks down into four keystroke pairs: C-A, A-N, N-O and O-E. These translate into the detection system
They say hackers could use a smartphone accelerometer to sense keyboard vibrations and decipher complete sentences with up to 80 percent accuracy.
"We first tried our experiments with an iPhone 3GS, and the results were difficult to read," says assistant professor Patrick Traynor.
"But then we tried an iPhone 4, which has an added gyroscope to clean up the accelerometer noise, and the results were much better. We believe that most smartphones made in the past two years are sophisticated enough to launch this attack."
The technique works through probability and by detecting pairs of keystrokes, rather than individual keys. It models 'keyboard events' in pairs, then determines whether the pair of keys pressed is on the left or the right side of the keyboard, and whether they're close together or far apart.
It then compares the results against a preloaded dictionary, each word of which has been broken down by similar measurements. The technique only works reliably on words of three or more letters.
For example, the word 'canoe' breaks down into four keystroke pairs: C-A, A-N, N-O and O-E. These translate into the detection system