Advances in logistics, operations, and management science book series,
Год журнала:
2023,
Номер
unknown, С. 36 - 74
Опубликована: Дек. 29, 2023
This
chapter
explores
the
topic
of
a
novel
network-based
intrusion
detection
system
(NIDPS)
that
utilises
concept
graph
theory
to
detect
and
prevent
incoming
threats.
With
technology
progressing
at
rapid
rate,
number
cyber
threats
will
also
increase
accordingly.
Thus,
demand
for
better
network
security
through
NIDPS
is
needed
protect
data
contained
in
networks.
The
primary
objective
this
explore
based
four
different
aspects:
collection,
analysis
engine,
preventive
action,
reporting.
Besides
analysing
existing
NIDS
technologies
market,
various
research
papers
journals
were
explored.
authors'
solution
covers
basic
structure
an
system,
from
collecting
processing
generating
alerts
reports.
Data
collection
methods
like
packet-based,
flow-based,
log-based
collections
terms
scale
viability.
Computers,
Год журнала:
2025,
Номер
14(2), С. 61 - 61
Опубликована: Фев. 11, 2025
With
the
proliferation
of
IoT-based
applications,
security
requirements
are
becoming
increasingly
stringent.
Given
diversity
such
systems,
selecting
most
appropriate
solutions
and
technologies
to
address
challenges
is
a
complex
activity.
This
paper
provides
an
exhaustive
evaluation
existing
related
IoT
domain,
analysing
studies
published
between
2021
2025.
review
explores
evolving
landscape
security,
identifying
key
focus
areas,
challenges,
proposed
as
presented
in
recent
research.
Through
this
analysis,
categorizes
efforts
into
six
main
areas:
emerging
(35.2%
studies),
securing
identity
management
(19.3%),
attack
detection
(17.9%),
data
protection
(8.3%),
communication
networking
(13.8%),
risk
(5.5%).
These
percentages
highlight
research
community’s
indicate
areas
requiring
further
investigation.
From
leveraging
machine
learning
blockchain
for
anomaly
real-time
threat
response
optimising
lightweight
algorithms
resource-limited
devices,
researchers
propose
innovative
adaptive
threats.
The
underscores
integration
advanced
enhance
system
while
also
highlighting
ongoing
challenges.
concludes
with
synthesis
threats
each
identified
category,
along
their
solutions,
aiming
support
decision-making
during
design
approach
applications
guide
future
toward
comprehensive
efficient
frameworks.
PLoS ONE,
Год журнала:
2025,
Номер
20(2), С. e0316253 - e0316253
Опубликована: Фев. 12, 2025
Intrusion
detection
plays
a
significant
role
in
the
provision
of
information
security.
The
most
critical
element
is
ability
to
precisely
identify
different
types
intrusions
into
network.
However,
poses
important
challenge,
as
many
new
intrusion
are
now
generated
by
cyber-attackers
every
day.
A
robust
system
still
elusive,
despite
various
strategies
that
have
been
proposed
recent
years.
Hence,
novel
deep-learning-based
architecture
for
detecting
computer
network
this
paper.
aim
construct
hybrid
enhances
efficiency
and
accuracy
detection.
main
contribution
our
work
deep
learning-based
which
PSO
used
hyperparameter
optimisation
three
well-known
pre-trained
models
combined
an
optimised
way.
suggested
method
involves
six
key
stages:
data
gathering,
pre-processing,
neural
(DNN)
design,
hyperparameters,
training,
evaluation
trained
DNN.
To
verify
superiority
over
alternative
state-of-the-art
schemes,
it
was
evaluated
on
KDDCUP’99,
NSL-KDD
UNSW-NB15
datasets.
Our
empirical
findings
show
model
successfully
correctly
classifies
attacks
with
82.44%,
90.42%
93.55%
values
obtained
UNSW-B15,
KDDCUP’99
datasets,
respectively,
outperforms
schemes
literature.
Computers,
Год журнала:
2025,
Номер
14(3), С. 87 - 87
Опубликована: Март 3, 2025
The
rapid
growth
of
digital
communications
and
extensive
data
exchange
have
made
computer
networks
integral
to
organizational
operations.
However,
this
increased
connectivity
has
also
expanded
the
attack
surface,
introducing
significant
security
risks.
This
paper
provides
a
comprehensive
review
Intrusion
Detection
System
(IDS)
technologies
for
network
security,
examining
both
traditional
methods
recent
advancements.
covers
IDS
architectures
types,
key
detection
techniques,
datasets
test
environments,
implementations
in
modern
environments
such
as
cloud
computing,
virtualized
networks,
Internet
Things
(IoT),
industrial
control
systems.
It
addresses
current
challenges,
including
scalability,
performance,
reduction
false
positives
negatives.
Special
attention
is
given
integration
advanced
like
Artificial
Intelligence
(AI)
Machine
Learning
(ML),
potential
distributed
blockchain.
By
maintaining
broad-spectrum
analysis,
aims
offer
holistic
view
state-of-the-art
IDSs,
support
diverse
audience,
identify
future
research
development
directions
critical
area
cybersecurity.
Advances in logistics, operations, and management science book series,
Год журнала:
2023,
Номер
unknown, С. 36 - 74
Опубликована: Дек. 29, 2023
This
chapter
explores
the
topic
of
a
novel
network-based
intrusion
detection
system
(NIDPS)
that
utilises
concept
graph
theory
to
detect
and
prevent
incoming
threats.
With
technology
progressing
at
rapid
rate,
number
cyber
threats
will
also
increase
accordingly.
Thus,
demand
for
better
network
security
through
NIDPS
is
needed
protect
data
contained
in
networks.
The
primary
objective
this
explore
based
four
different
aspects:
collection,
analysis
engine,
preventive
action,
reporting.
Besides
analysing
existing
NIDS
technologies
market,
various
research
papers
journals
were
explored.
authors'
solution
covers
basic
structure
an
system,
from
collecting
processing
generating
alerts
reports.
Data
collection
methods
like
packet-based,
flow-based,
log-based
collections
terms
scale
viability.
