International Journal of Information Systems and Supply Chain Management,
Journal Year:
2024,
Volume and Issue:
17(1), P. 1 - 15
Published: June 5, 2024
E-commerce
has
grown
quickly
in
recent
years
thanks
to
advancements
Internet
and
information
technologies.
For
the
majority
of
consumers,
online
shopping
emerged
as
a
primary
mode
shopping.
However,
it
become
more
challenging
for
businesses
satisfy
consumer
demand
due
their
increasingly
individualized
wants.
To
address
need
customized
products
with
numerous
kinds
small
quantities,
must
rebuild
supply
chain
systems
increase
efficiency
adaptability.
The
SI-LSF
technique,
which
employs
boosting
learning
target-relative
feature
space
lower
prediction
error
enhance
algorithm's
capacity
handle
input-output
interactions,
is
validated
this
study
using
genuine
industrial
dataset.
successfully
identifies
relationship
between
sales
well
target-specific
features
by
applying
multi-objective
regression
integration
algorithm
based
on
label-specific
real-world
scenario.
Transactions on Emerging Telecommunications Technologies,
Journal Year:
2024,
Volume and Issue:
35(11)
Published: Oct. 20, 2024
ABSTRACT
Botnets
have
emerged
as
a
significant
internet
security
threat,
comprising
networks
of
compromised
computers
under
the
control
command
and
(C&C)
servers.
These
malevolent
entities
enable
range
malicious
activities,
from
denial
service
(DoS)
attacks
to
spam
distribution
phishing.
Each
bot
operates
binary
code
on
vulnerable
hosts,
granting
remote
attackers
who
can
harness
combined
processing
power
these
hosts
for
synchronized,
highly
destructive
while
maintaining
anonymity.
This
survey
explores
botnets
their
evolution,
covering
aspects
such
life
cycles,
C&C
models,
botnet
communication
protocols,
detection
methods,
unique
environments
operate
in,
strategies
evade
tools.
It
analyzes
research
challenges
future
directions
related
botnets,
with
particular
focus
evasion
techniques,
including
methods
like
encryption
use
covert
channels
reinforcement
botnets.
By
reviewing
existing
research,
provides
comprehensive
overview
origins
evolving
tactics,
evaluates
how
counteract
activities.
Its
primary
goal
is
inform
community
about
changing
landscape
in
combating
threats,
offering
guidance
addressing
concerns
effectively
through
highlighting
methods.
The
concludes
by
presenting
directions,
using
strengthen
aims
guide
researchers
developing
more
robust
measures
combat
effectively.
Internet of Things and Cyber-Physical Systems,
Journal Year:
2024,
Volume and Issue:
4, P. 258 - 267
Published: Jan. 1, 2024
The
significance
of
intrusion
detection
systems
in
networks
has
grown
because
the
digital
revolution
and
increased
operations.
method
classifies
network
traffic
as
threat
or
normal
based
on
data
features.
Intrusion
system
faces
a
trade-off
between
various
parameters
such
accuracy,
relevance,
redundancy,
false
alarm
rate,
other
objectives.
paper
presents
systematic
review
Internet
Things
(IoT)
using
multi-objective
optimization
algorithms
(MOA),
to
identify
attempts
at
exploiting
security
vulnerabilities
reducing
chances
attacks.
MOAs
provide
set
optimized
solutions
for
process
highly
complex
IoT
networks.
This
identification
multiple
objectives
detection,
comparative
analysis
their
approaches,
datasets
used
evaluation.
show
encouraging
potential
enhance
conflicting
detection.
Additionally,
current
challenges
future
research
ideas
are
identified.
In
addition
demonstrating
new
advancements
techniques,
this
study
gaps
that
can
be
addressed
while
designing
PLoS ONE,
Journal Year:
2024,
Volume and Issue:
19(1), P. e0295801 - e0295801
Published: Jan. 24, 2024
The
escalating
prevalence
of
cybersecurity
risks
calls
for
a
focused
strategy
in
order
to
attain
efficient
resolutions.
This
study
introduces
detection
model
that
employs
tailored
methodology
integrating
feature
selection
using
SHAP
values,
shallow
learning
algorithm
called
PV-DM,
and
machine
classifiers
like
XGBOOST.
efficacy
our
suggested
is
highlighted
by
employing
the
NSL-KDD
UNSW-NB15
datasets.
Our
approach
dataset
exhibits
exceptional
performance,
with
an
accuracy
98.92%,
precision
recall
95.44%,
F1-score
96.77%.
Notably,
this
performance
achieved
utilizing
only
four
characteristics,
indicating
efficiency
approach.
proposed
achieves
82.86%,
84.07%,
77.70%,
80.20%
dataset,
six
features.
research
findings
provide
substantial
evidence
enhanced
compared
traditional
deep-learning
across
all
metrics.
Biomimetics,
Journal Year:
2023,
Volume and Issue:
9(1), P. 9 - 9
Published: Dec. 25, 2023
Feature
selection
is
becoming
a
relevant
problem
within
the
field
of
machine
learning.
The
feature
focuses
on
small,
necessary,
and
sufficient
subset
features
that
represent
general
set
features,
eliminating
redundant
irrelevant
information.
Given
importance
topic,
in
recent
years
there
has
been
boom
study
problem,
generating
large
number
related
investigations.
this,
this
work
analyzes
161
articles
published
between
2019
2023
(20
April
2023),
emphasizing
formulation
performance
measures,
proposing
classifications
for
objective
functions
evaluation
metrics.
Furthermore,
an
in-depth
description
analysis
metaheuristics,
benchmark
datasets,
practical
real-world
applications
are
presented.
Finally,
light
advances,
review
paper
provides
future
research
opportunities.
