2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW),
Год журнала:
2024,
Номер
unknown, С. 827 - 828
Опубликована: Март 16, 2024
Gender
identification
of
virtual
reality
(VR)
users
by
machine
learning
tracking
data
could
afford
personalized
experiences,
including
mitigation
expected
human
factors
or
psychology
issues.
While
much
research
has
recently
been
conducted
to
identify
individual
given
their
VR
data,
little
investigated
gender
identification.
Furthermore,
nearly
all
prior
studies
have
only
considered
positions
and
rotations
the
devices.
We
present
a
systematic
investigation
different
combinations
spatial
representations
tracked
devices
for
predicting
user's
gender.
Our
results
indicate
head
are
integral
while
surprisingly
not
as
important.
This
research
paper
explores
the
pioneering
role
of
augmented
reality
(AR)
and
virtual
(VR)
in
reshaping
medical
education
within
metaverse,
focusing
particularly
on
their
remarkable
benefits
for
individuals
with
disabilities.
examines
how
these
immersive
technologies
can
be
customized
to
meet
unique
needs
those
disabilities,
including
mobility.
It
demonstrates
AR
VR
enable
actively
participate
simulations,
offering
them
a
deeper
understanding
intricate
procedures.
article
highlights
critical
importance
ethical
considerations,
privacy
measures,
adherence
accessibility
standards
deployment
training
robust
framework
harnessing
transformative
capabilities
health
education.
delves
into
various
ways
which
facilitate
experiential
learning,
providing
an
immersive,
hands-on
approach
supporting
remote
diagnostics
mental
services,
showcasing
capability
enhance
doctor–patient
interactions
support.
represents
that
metaverse
have
potential
empower
leading
more
inclusive
effective
training.
Journal of Network and Computer Applications,
Год журнала:
2024,
Номер
231, С. 103989 - 103989
Опубликована: Авг. 2, 2024
The
metaverse
is
a
nascent
concept
that
envisions
virtual
universe,
collaborative
space
where
individuals
can
interact,
create,
and
participate
in
wide
range
of
activities.
Privacy
the
critical
concern
as
evolves
immersive
experiences
become
more
prevalent.
privacy
problem
refers
to
challenges
concerns
surrounding
personal
information
data
within
Virtual
Reality
(VR)
environments
shared
VR
becomes
accessible.
Metaverse
will
harness
advancements
from
various
technologies
such
Artificial
Intelligence
(AI),
Extended
(XR)
Mixed
(MR)
provide
personalized
services
its
users.
Moreover,
enable
experiences,
relies
on
collection
fine-grained
user
leads
issues.
Therefore,
before
potential
be
fully
realized,
related
must
addressed.
This
includes
safeguarding
users'
control
over
their
data,
ensuring
security
information,
protecting
in-world
actions
interactions
unauthorized
sharing.
In
this
paper,
we
explore
future
metaverses
are
expected
face,
given
reliance
AI
for
tracking
users,
creating
XR
MR
facilitating
interactions.
thoroughly
analyze
technical
solutions
differential
privacy,
Homomorphic
Encryption,
Federated
Learning
discuss
sociotechnical
issues
regarding
privacy.
Proceedings on Privacy Enhancing Technologies,
Год журнала:
2023,
Номер
2023(4), С. 238 - 256
Опубликована: Авг. 3, 2023
Fifty
study
participants
playtested
an
innocent-looking
"escape
room"
game
in
virtual
reality
(VR).
Within
just
a
few
minutes,
adversarial
program
had
accurately
inferred
over
25
of
their
personal
data
attributes,
from
anthropometrics
like
height
and
wingspan
to
demographics
age
gender.
As
notoriously
data-hungry
companies
become
increasingly
involved
VR
development,
this
experimental
scenario
may
soon
represent
typical
user
experience.
Since
the
Cambridge
Analytica
scandal
2018,
adversarially-designed
gamified
elements
have
been
known
constitute
significant
privacy
threat
conventional
social
platforms.
In
work,
we
present
case
how
metaverse
environments
can
similarly
be
adversarially
constructed
covertly
infer
dozens
attributes
seemingly-anonymous
users.
While
existing
research
largely
focuses
on
passive
observation,
argue
that
because
individuals
subconsciously
reveal
information
via
motion
response
specific
stimuli,
active
attacks
pose
outsized
risk
environments.
Proceedings on Privacy Enhancing Technologies,
Год журнала:
2023,
Номер
2024(1), С. 21 - 40
Опубликована: Окт. 22, 2023
The
adoption
of
virtual
reality
(VR)
technologies
has
rapidly
gained
momentum
in
recent
years
as
companies
around
the
world
begin
to
position
so-called
''metaverse''
next
major
medium
for
accessing
and
interacting
with
internet.
While
consumers
have
become
accustomed
a
degree
data
harvesting
on
web,
real-time
nature
sharing
metaverse
indicates
that
privacy
concerns
are
likely
be
even
more
prevalent
new
''Web
3.0.''
Research
into
VR
demonstrated
plethora
sensitive
personal
information
is
observable
by
various
would-be
adversaries
from
just
few
minutes
telemetry
data.
On
other
hand,
we
yet
see
parallels
many
privacy-preserving
tools
aimed
at
mitigating
threats
conventional
platforms.
This
paper
aims
systematize
knowledge
landscape
countermeasures
proposing
comprehensive
taxonomy
attributes,
protections,
based
study
74
collected
publications.
We
complement
our
qualitative
discussion
statistical
analysis
risk
associated
sources
inherent
consideration
known
attacks
defenses.
By
focusing
highlighting
clear
outstanding
opportunities,
hope
motivate
guide
further
research
this
increasingly
important
field.
IEEE Transactions on Visualization and Computer Graphics,
Год журнала:
2024,
Номер
30(5), С. 2239 - 2246
Опубликована: Март 4, 2024
Extended
reality
(XR)
devices
such
as
the
Meta
Quest
and
Apple
Vision
Pro
have
seen
a
recent
surge
in
attention,
with
motion
tracking
"telemetry"
data
lying
at
core
of
nearly
all
XR
metaverse
experiences.
Researchers
are
just
beginning
to
understand
implications
this
for
security,
privacy,
usability,
more,
but
currently
lack
large-scale
human
datasets
study.
The
BOXRR-23
dataset
contains
4,717,215
capture
recordings,
voluntarily
submitted
by
105,852
device
users
from
over
50
countries.
is
200
times
larger
than
largest
existing
research
uses
new,
highly
efficient
purpose-built
Open
Recording
(XROR)
file
format.
2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW),
Год журнала:
2024,
Номер
unknown, С. 493 - 500
Опубликована: Март 16, 2024
Virtual
reality
(VR)
and
"metaverse"
systems
have
recently
seen
a
resurgence
in
interest
investment
as
major
technology
companies
continue
to
enter
the
space.
However,
recent
studies
demonstrated
that
motion
tracking
"telemetry"
data
used
by
nearly
all
VR
applications
is
uniquely
identifiable
fingerprint
scan,
raising
significant
privacy
concerns
surrounding
metaverse
technologies.
In
this
paper,
we
propose
new
"deep
masking"
approach
scalably
facilitates
real-time
anonymization
of
telemetry
data.
Through
large-scale
user
study
$(N=182)$
,
demonstrate
our
method
significantly
more
usable
private
than
existing
anonymity
systems.
Behavioral
Biometrics
in
Virtual
Reality
(VR)
enable
implicit
user
identification
by
leveraging
the
motion
data
of
users'
heads
and
hands
from
their
interactions
VR.
This
spatiotemporal
forms
a
Kinetic
Signature,
which
is
user-dependent
behavioral
biometric
trait.
Although
kinetic
signatures
have
been
widely
used
recent
research,
factors
contributing
to
degree
identifiability
remain
mostly
unexplored.
Drawing
existing
literature,
this
work
systematically
examines
influence
static
dynamic
components
human
motion.
We
conducted
study
(N
=
24)
with
two
sessions
reidentify
users
across
different
VR
sports
exercises
after
one
week.
found
that
signature
depends
on
its
inherent
factors,
best
combination
allowing
for
90.91%
accuracy
week
had
passed.
Therefore,
lays
foundation
designing
refining
movement-based
protocols
immersive
environments.
