International Journal of Wireless and Microwave Technologies,
Journal Year:
2024,
Volume and Issue:
14(2), P. 55 - 66
Published: April 1, 2024
In
the
dynamic
realm
of
Smart
Healthcare
Systems
(SHS),
integration
IoT
devices
has
revolutionized
conventional
practices,
ushering
in
an
era
real-time
data
collection
and
seamless
communication
across
healthcare
ecosystem.
Amidst
this
technological
shift,
paramount
concern
remains
security
sensitive
within
intricate
networks.
Several
cryptographic
algorithms
have
been
proposed
for
smart
systems
protection
critical
SHS,
however,
majority
newly
shortcomings
terms
resource
utilization
level
that
they
provide.
Our
research
delves
into
existing
highly
secure
provides
a
comparative
analysis
two
popular
viz
N-th
Degree
Truncated
Polynomial
Ring
(NTRU)
Elliptic
Curve
Cryptography
(ECC)
verifies
their
applicability
SHS.
Recognizing
ECC's
compact
key
sizes
its
vulnerability
to
quantum
computing
threats,
our
study
finds
NTRU
as
resilient
quantum-resistant
alternative,
providing
robust
defense
mechanism
evolving
landscape
cybersecurity.
Key
findings
underscore
efficacy
safeguarding
data,
emphasizing
superior
performance
compared
ECC,
especially
face
emerging
challenges.
The
depicts
ECC
excels
generation
speed,
delivering
efficient
swift
creation.
However,
it
requires
larger
keys
withstand
potential
vulnerabilities.
On
other
hand,
time
is
slightly
more
than
but
being
quantum-resistant,
high
security.
Blockchain Research and Applications,
Journal Year:
2023,
Volume and Issue:
5(2), P. 100178 - 100178
Published: Dec. 20, 2023
Protecting
private
data
in
smart
homes,
a
popular
Internet-of-Things
(IoT)
application,
remains
significant
security
and
privacy
challenge
due
to
the
large-scale
development
distributed
nature
of
IoT
networks.
Recently,
healthcare
has
leveraged
home
systems,
thereby
compounding
concerns
terms
confidentiality
sensitive
by
extension
owner.
However,
PoA-based
Blockchain
DLT
emerged
as
promising
solution
for
protecting
from
indiscriminate
use
preserving
individuals
residing
IoT-enabled
homes.
This
review
elicits
some
concerns,
issues,
problems
that
have
hindered
adoption
blockchain
(BCoT)
domains
suggests
requisite
solutions
using
aging-in-place
scenario.
Implementation
issues
with
BCoT
were
examined
well
combined
challenges
can
pose
when
utilised
gains.
The
study
discusses
recent
findings,
opportunities,
barriers,
provide
recommendations
could
facilitate
continuous
growth
application
healthcare.
Lastly,
then
explored
potential
permission
an
applicable
consent-based
model
decision-making
information
disclosure
process,
including
publisher-subscriber
contracts
fine-grained
access
control
ensure
secure
processing
sharing,
ethical
trust
personal
disclosure,
direction.
proposed
authorisation
framework
guarantee
ownership,
conditional
management,
scalable
tamper-proof
storage,
more
resilient
system
against
threat
models
such
interception
insider
attacks.
Scientific Reports,
Journal Year:
2025,
Volume and Issue:
15(1)
Published: Jan. 2, 2025
This
study
presents
a
novel
privacy-preserving
self-supervised
(SSL)
framework
for
COVID-19
classification
from
lung
CT
scans,
utilizing
federated
learning
(FL)
enhanced
with
Paillier
homomorphic
encryption
(PHE)
to
prevent
third-party
attacks
during
training.
The
FL-SSL
based
employs
two
publicly
available
scan
datasets
which
are
considered
as
labeled
and
an
unlabeled
dataset.
dataset
is
split
into
three
subsets
assumed
be
collected
hospitals.
Training
done
using
the
Bootstrap
Your
Own
Latent
(BYOL)
contrastive
SSL
VGG19
encoder
followed
by
attention
CNN
blocks
(VGG19
+
CNN).
input
processed
selecting
largest
portion
of
each
automated
selection
approach
64
×
size
utilized
reduce
computational
complexity.
Healthcare
privacy
issues
addressed
collaborative
training
across
decentralized
secure
aggregation
PHE,
underscoring
effectiveness
this
approach.
Three
used
train
local
BYOL
model,
together
optimizes
central
encoder.
employed
(updated
CNN),
resulting
in
accuracy
97.19%,
precision
97.43%,
recall
98.18%.
reliability
framework's
performance
demonstrated
through
statistical
analysis
five-fold
cross-validation.
efficacy
proposed
further
showcased
showing
its
on
distinct
modality
datasets:
skin
cancer,
breast
chest
X-rays.
In
conclusion,
offers
promising
solution
accurate
diagnosis
X-rays,
preserving
overcoming
challenges
scarcity
Transactions on Emerging Telecommunications Technologies,
Journal Year:
2025,
Volume and Issue:
36(3)
Published: March 1, 2025
ABSTRACT
Large‐scale
healthcare
systems
face
significant
challenges
in
ensuring
security
and
privacy
when
sharing
vast
amounts
of
data
across
various
e‐health
entities.
Existing
studies
often
struggle
with
high
processing
costs,
latency,
energy
consumption,
delayed
response
times.
To
address
these
issues,
this
research
proposes
a
novel
Blockchain‐Assisted
Improved
Puma
Edge
Computing
Network
(BA‐IPEN)
for
efficient
secure
management.
The
proposed
model
integrates
three
key
modules:
collection
at
the
IoT
layer,
edge
storage
cloud
layer.
Patient
physiological
are
gathered
from
sensors
transmitted
to
devices
through
remote
gateway
devices.
At
Modified
Optimization
Algorithm
(POA)
is
employed
maximize
resource
utilization
while
minimizing
consumption
latency.
Additionally,
computing
performs
preprocessing
tasks
such
as
missing
filtering
normalization
extract
valuable
insights
raw
sensor
data,
thereby
enhancing
overall
performance.
For
storage,
TwoFish
used.
This
algorithm
encrypts
collected
bolstering
security.
Blockchain
technology
ensures
tamper‐proof
records
transparent
access
restrictions
by
providing
decentralized
immutable
ledger
securely
storing
cloud.
Extensive
experiments
demonstrate
effectiveness
BA‐IPEN
model,
revealing
reductions
computational
cost
latency
cloud‐based
storage.
Experimental
results
also
confirm
superiority
over
traditional
mechanisms,
showcasing
improvements
performance
indicators
reduced
consumption.
