Ensemble-Based Deep Learning Models for Enhancing IoT Intrusion Detection
Applied Sciences,
Journal Year:
2023,
Volume and Issue:
13(21), P. 11985 - 11985
Published: Nov. 2, 2023
Cybersecurity
finds
widespread
applications
across
diverse
domains,
encompassing
intelligent
industrial
systems,
residential
environments,
personal
gadgets,
and
automobiles.
This
has
spurred
groundbreaking
advancements
while
concurrently
posing
persistent
challenges
in
addressing
security
concerns
tied
to
IoT
devices.
intrusion
detection
involves
using
sophisticated
techniques,
including
deep
learning
models
such
as
convolutional
neural
networks
(CNNs),
recurrent
(RNNs),
anomaly
algorithms,
identify
unauthorized
or
malicious
activities
within
ecosystems.
These
systems
continuously
monitor
analyze
network
traffic
device
behavior,
seeking
patterns
that
deviate
from
established
norms.
When
anomalies
are
detected,
measures
triggered
thwart
potential
threats.
is
vital
for
safeguarding
data
integrity,
ensuring
users’
privacy,
maintaining
critical
systems’
reliability
safety.
As
the
landscape
evolves,
effective
mechanisms
become
increasingly
essential
mitigate
ever-growing
spectrum
of
cyber
Practical
approaches,
notably
learning-based
detection,
have
been
introduced
tackle
these
issues.
study
utilizes
models,
long
short-term
memory
(LSTM),
gated
units
(GRUs),
introducing
an
ensemble
architectural
framework
integrates
a
voting
policy
model’s
structure,
thereby
facilitating
computation
hierarchical
patterns.
In
our
analysis,
we
compared
performance
classifiers
with
traditional
techniques.
The
standout
were
CNN-LSTM
CNN-GRU,
achieving
impressive
accuracies
99.7%
99.6%,
along
exceptional
F1-scores
0.998
0.997,
respectively.
Language: Английский
Machine Learning for Healthcare-IoT Security: A Review and Risk Mitigation
IEEE Access,
Journal Year:
2023,
Volume and Issue:
11, P. 145869 - 145896
Published: Jan. 1, 2023
The
Healthcare
Internet-of-Things
(H-IoT),
commonly
known
as
Digital
Healthcare,
is
a
data-driven
infrastructure
that
highly
relies
on
smart
sensing
devices
(i.e.,
blood
pressure
monitors,
temperature
sensors,
etc.)
for
faster
response
time,
treatments,
and
diagnosis.
However,
with
the
evolving
cyber
threat
landscape,
IoT
have
become
more
vulnerable
to
broader
risk
surface
(e.g.,
risks
associated
generative
AI,
5G-IoT,
etc.),
which,
if
exploited,
may
lead
data
breaches,
unauthorized
access,
lack
of
command
control
potential
harm.
This
paper
reviews
fundamentals
healthcare
IoT,
its
privacy,
security
challenges
machine
learning
H-IoT
devices.
further
emphasizes
importance
monitoring
layers
such
perception,
network,
cloud,
application.
Detecting
responding
anomalies
involves
various
cyber-attacks
protocols
Wi-Fi
6,
Narrowband
Internet
Things
(NB-IoT),
Bluetooth,
ZigBee,
LoRa,
5G
New
Radio
(5G
NR).
A
robust
authentication
mechanism
based
deep
techniques
required
protect
mitigate
from
increasing
cybersecurity
vulnerabilities.
Hence,
in
this
review
paper,
privacy
mitigation
strategies
building
resilience
are
explored
reported.
Language: Английский
The Future of Ethical Hacking: Charting the Uncharted in Cybersecurity
Gleuto M. Serafim
No information about this author
Lecture notes in networks and systems,
Journal Year:
2025,
Volume and Issue:
unknown, P. 17 - 30
Published: Jan. 1, 2025
Language: Английский
Efficient Data Collaboration Using Multi-Party Privacy Preserving Machine Learning Framework
IEEE Access,
Journal Year:
2023,
Volume and Issue:
11, P. 138151 - 138164
Published: Jan. 1, 2023
In
a
modern
era
where
data-driven
insights
are
the
foundation
of
technological
advancements
preserving
privacy
and
security
sensitive
information
while
harnessing
collective
intelligence
multiple
parties
is
imperative.
This
research
presents
Secure
Collaborative
Learning
Algorithm
(SCLA)
designed
to
facilitate
efficient
multi-party
machine
learning
without
compromising
data
privacy.
Our
focus
on
leveraging
existing,
secure
databases
requiring
an
additional
collection
process.
SCLA
seamlessly
integrates
homomorphic
encryption
Federated
(FL)
enable
collaboration
among
various
stakeholders.
The
proposed
algorithm
aggregates
model
updates
in
privacy-preserving
manner,
demonstrating
enhanced
accuracy,
competitive
convergence
speed,
robust
scalability.
By
carefully
balancing
preservation
efficiency,
showcases
promising
avenue
for
privacy-focused
collaborative
using
existing
repositories.
Language: Английский
Assessing the Landscape of Mobile Data Vulnerabilities: A Comprehensive Review
2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES),
Journal Year:
2023,
Volume and Issue:
unknown, P. 79 - 87
Published: April 28, 2023
The
widespread
adoption
of
mobile
devices
in
recent
years
has
made
them
an
integral
part
our
daily
lives.
However,
with
the
increased
usage
for
sensitive
data
transactions,
threat
vulnerabilities
also
grown
significantly.
This
paper
presents
a
comprehensive
review
landscape
to
help
researchers
and
practitioners
understand
current
state
security
identify
potential
areas
improvement.
starts
by
defining
term
"mobile
vulnerability"
explaining
various
types
that
can
affect
devices,
including
network-based,
software-based,
physical
vulnerabilities.
It
then
reviews
literature
on
provides
in-depth
analysis
latest
research
findings,
trends,
emerging
threats.
examines
mitigation
techniques
have
been
proposed
address
vulnerabilities,
such
as
secure
coding
practices,
intrusion
detection
systems,
device
hardening
measures.
Additionally,
highlights
challenges
limitations
these
techniques,
discusses
need
more
integrated
approach
security.
Finally,
concludes
recommendations
future
directions
suggests
should
focus
developing
effective
efficient
methods
detecting
mitigating
well
improving
user
education
awareness
prevent
incidents.
Overall,
this
valuable
resource
interested
presenting
identifying
Language: Английский
Developing the Role of Firewalls in Enhancing Web Security for Wireless Networks
Ritushree Narayan,
No information about this author
N. V. Balaji,
No information about this author
G Kalanandhini
No information about this author
et al.
Published: Dec. 29, 2023
Firewalls
play
a
critical
role
in
controlling
incoming
and
outgoing
community
site
visitors
shielding
wireless
network
from
malicious
assaults.
This
technical
summary
focuses
on
the
development
of
firewalls
as
way
to
beautify
internet
safety
for
Wi-Fi
networks.
Contemporary
networks
are
increasingly
more
vulnerable
cyber-attacks.
one
simplest
strategies
safety,
able
restricting
among
or
net.
They
also
can
be
used
come
across
perceive
pastime.
The
has
improved
at
fast
pace
current
years.
New
functions
along
with
Intrusion
Detection
Prevention
systems
(IDS/IPS),
URL
filtering,
virus
scanning,
user
authentication,
application
layer
have
vastly
advanced
effectiveness
firewalls.
Advanced
such
deploy
Rector
Reactive
tracking
(IRM),
get
right
entry
manage
(NAC)
getting
detect
suspicious
requests
put
into
effect
coverage.
NAC
may
both
control
admission
resources,
respond
visitors.
enhanced
protection
supplied
by
is
useful
home
employer
Via
implementing
those
capabilities,
organizations
lessen
danger
cyberattacks
guard
their
resources.
Language: Английский