The
Industrial
Internet
of
Services
(IIoS)
combines
traditional
industrial
systems
with
digital
technologies,
offering
numerous
advantages
like
improved
efficiency,
productivity,
and
resource
optimization.
However,
the
rapid
growth
IIoS
introduces
significant
cybersecurity
risks.
Cyber
threats
including
DDoS
attacks,
unauthorized
access,
data
breaches,
malware
infections,
pose
a
severe
risk
to
security.
Among
these
threats,
attacks
have
become
concern.
overwhelm
networks
excessive
traffic,
preventing
legitimate
users
from
accessing
network.
Such
can
disrupt
systems,
causing
downtime
inaccessible
services.This
study
aims
analyze
that
target
explore
effectiveness
deep
learning
algorithms
in
detecting
DDoS.
This
research
analyzes
performance
four
algorithms,
ultimately
finding
DNN
GRU
models
achieved
remarkably
high
accuracy
rates
99%.
enhance
ability
identify
potential
Distributed
Denial
Service
(DDoS)
leading
operational
security
optimized
production
processes.
By
employing
findings
this
research,
effectively
detect
hazards,
resulting
enhanced
productivity
streamlined
processes
within
environment.
