最終更新日:2022/12/24
Allowing patterns to emerge from high dimensional unavoidably noisy data. The goal of this work is to raise awareness about the potential risks related to motion sensors built-in wearable devices and to demonstrate abuse opportunities leveraged by advanced neural network architectures. The LSTM-based implementation presented in this research can perform touchlogging and keylogging on 12-keys keypads with above-average accuracy even when confronted with raw unprocessed data.
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Allowing
patterns
to
emerge
from
high
dimensional
unavoidably
noisy
data.
The
goal
of
this
work
is
to
raise
awareness
about
the
potential
risks
related
to
motion
sensors
built-in
wearable
devices
and
to
demonstrate
abuse
opportunities
leveraged
by
advanced
neural
network
architectures.
The
LSTM-based
implementation
presented
in
this
research
can
perform
touchlogging
and
keylogging
on
12-keys
keypads
with
above-average
accuracy
even
when
confronted
with
raw
unprocessed
data.