In
recent
years,
vehicular
ad
hoc
networks
(VANETs)
have
faced
growing
security
concerns,
particularly
from
Denial
of
Service
(DoS)
and
Distributed
(DDoS)
attacks.
These
attacks
flood
the
network
with
malicious
traffic,
disrupting
services
compromising
resource
availability.
While
various
techniques
been
proposed
to
address
these
threats,
this
study
presents
an
optimized
framework
leveraging
advanced
deep-learning
models
for
improved
detection
accuracy.
The
Intrusion
Detection
System
(IDS)
employs
Convolutional
Neural
Networks
(CNN),
Long
Short-Term
Memory
(LSTM),
Deep
Belief
(DBN)
alongside
robust
feature
selection
techniques,
Random
Projection
(RP)
Principal
Component
Analysis
(PCA).
This
extracts
analyzes
significant
features
using
a
publicly
available
application-layer
DoS
attack
dataset,
achieving
higher
accuracy
than
traditional
methods.
Experimental
results
indicate
that
combining
CNN,
LSTM
networks,
DBN
like
PCA
in
classification
performance,
0.994,
surpassing
state-of-the-art
machine
learning
models.
novel
approach
enhances
reliability
safety
vehicle
communications
by
providing
efficient,
real-time
threat
detection.
findings
contribute
significantly
VANET
security,
laying
foundation
future
advancements
connected
protection.
Service Oriented Computing and Applications,
Год журнала:
2024,
Номер
unknown
Опубликована: Ноя. 21, 2024
Abstract
Product
Service
Systems
(PSSs)
introduce
new
business
models
for
enterprises
to
promote
tangible
products
along
with
intangible
functions
or
services,
thereby
incentivising
product
sustainability
profitability,
economic
stability
and
customer
satisfaction.
However,
the
unique
characteristics
of
a
PSS
challenge
obsolete
development
processes
demand
dynamic
change
in
complex
building
blocks
underlying
design
infrastructure
attain
high
quality
services.
This
implies
need
radical
team
structure
collaboration
model,
organizational
structure,
technical
process
by
taking
complete
life
cycle
into
consideration.
paper,
firstly,
identifies
features
that
capabilities
existing
frameworks
standard
PSS.
In
response,
are
proposed
address
challenges
relating
actors’
involvement,
technology
provision,
needs
workflow
modelling.
Secondly,
these
combined
one
comprehensive
collaborative
methodology
modifying
modelling
techniques.
An
assessment
framework
based
on
Goal-Question-Metrics
approach
McCall
Quality
Model
is
successfully
used
evaluate
subsequently,
developed
through
use-case
study
analysis.
Symmetry,
Год журнала:
2024,
Номер
16(12), С. 1632 - 1632
Опубликована: Дек. 9, 2024
A
novel,
precise
disturbance
rejection
dynamic
inversion
control
algorithm
has
been
proposed.
In
the
high-order
surface
system,
an
innovative
approach
utilizes
a
monotonically
increasing
inverse
hyperbolic
sine
function
to
construct
extended
state
observer,
which
estimates
uncertain
functions
at
each
step.
The
monotonicity
of
simplifies
system
stability
analysis.
Additionally,
being
smooth
function,
it
avoids
disturbances
caused
by
piecewise
their
breakpoints
in
conventional
observer
construction,
thereby
enhancing
stability.
accurate
prediction
capability
new
improves
system’s
performance.
To
address
inherent
differential
explosion
phenomenon
traditional
schemes,
this
paper
ingeniously
employs
tracking
signal
as
substitute
for
filters,
thus
avoiding
that
may
occur
with
first-order
filters.
Finally,
comparative
simulations
were
conducted
validate
effectiveness
proposed
method.
results
show
both
and
controller
possess
high-gain
characteristics,
closed-loop
exhibits
fast
convergence
rate.
