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ta
n
c
e
s
,
i
n
t
r
u
s
i
o
n
s
m
a
y
b
e
t
r
i
g
g
e
r
e
d
b
y
i
n
t
e
r
n
a
l
l
y
a
u
t
h
o
r
i
z
e
d
p
e
r
s
o
n
n
e
l
w
h
o
c
a
r
r
y
o
u
t
t
h
es
e
a
s
s
a
u
l
ts
b
y
a
b
u
s
i
n
g
t
h
ei
r
a
u
t
h
o
r
i
t
y
a
n
d
m
o
v
i
n
g
o
u
t
s
i
d
e
t
h
ei
r
a
u
t
h
o
r
i
z
a
t
i
o
n
a
r
e
a
[
4
]
.
P
l
a
t
f
o
r
m
s
f
o
r
e
n
d
p
o
i
n
t
d
e
t
e
c
t
i
o
n
a
n
d
r
es
p
o
n
s
e
a
s
s
is
t
s
e
c
u
r
i
t
y
te
a
m
s
i
n
l
o
c
a
ti
n
g
s
u
s
p
i
c
i
o
u
s
b
e
h
a
v
i
o
r
o
n
e
n
d
p
o
i
n
t
s
,
w
h
i
c
h
e
n
a
b
l
e
s
t
h
em
t
o
e
r
a
d
i
c
a
t
e
t
h
r
e
a
ts
m
o
r
e
r
ap
i
d
l
y
a
n
d
r
e
d
u
c
e
t
h
e
d
a
m
a
g
e
c
a
u
s
e
d
b
y
a
n
a
t
ta
c
k
.
T
h
e
t
e
r
m
“
e
n
d
p
o
i
n
t
d
e
te
c
t
i
o
n
an
d
r
e
s
p
o
n
s
e
”
r
e
f
e
r
s
t
o
a
g
r
o
u
p
o
f
t
e
c
h
n
i
q
u
e
s
t
h
at
a
r
e
u
s
e
d
t
o
id
e
n
t
i
f
y
a
n
d
e
v
a
l
u
a
te
p
o
t
e
n
t
i
a
l
d
a
n
g
e
r
s
p
o
s
e
d
b
y
e
n
d
p
o
i
n
t
s
.
T
h
e
f
u
n
c
t
i
o
n
s
o
f
d
e
te
c
ti
o
n
,
i
n
v
e
s
t
i
g
a
t
i
o
n
,
t
h
r
e
a
t
h
u
n
t
in
g
,
a
n
d
r
e
a
c
t
i
o
n
a
r
e
o
f
t
e
n
i
n
c
l
u
d
e
d
i
n
a
n
E
DR
t
o
o
l
’
s
f
e
at
u
r
e
s
e
t
[
5
]
.
A
n
I
DS
i
s
a
u
s
e
f
u
l
a
d
j
u
n
c
t
t
o
a
f
i
r
e
wa
l
l
s
i
n
c
e
i
t
e
n
a
b
l
es
c
o
m
p
r
e
h
e
n
s
i
v
e
i
n
s
p
e
ct
i
o
n
s
o
f
d
a
t
a
p
a
c
k
e
t
s
’
h
e
a
d
e
r
s
a
s
w
el
l
as
t
h
e
i
r
c
o
n
t
e
n
ts
,
o
f
f
e
r
i
n
g
p
r
o
t
e
c
t
i
o
n
a
g
a
i
n
s
t
as
s
a
u
l
ts
t
h
a
t
a
f
i
r
ew
a
ll
m
a
y
o
t
h
e
r
wi
s
e
m
i
s
i
n
t
e
r
p
r
e
t
as
a
p
p
a
r
e
n
t
l
y
h
a
r
m
l
e
s
s
n
e
tw
o
r
k
t
r
a
f
f
i
c
[
6
]
.
D
e
e
p
l
e
a
r
n
i
n
g
-
b
as
e
d
i
n
t
r
u
s
i
o
n
d
e
t
e
c
ti
o
n
a
n
d
p
r
e
v
e
n
t
i
o
n
s
y
s
t
e
m
(
D
L
I
D
)
t
h
a
t
d
e
te
c
ts
t
h
e
i
n
t
r
u
s
i
o
n
e
f
f
i
c
i
e
n
t
l
y
.
T
h
is
m
e
c
h
a
n
i
s
m
u
t
i
li
z
es
t
h
e
d
e
e
p
l
e
a
r
n
i
n
g
a
l
g
o
r
i
t
h
m
t
o
s
e
p
a
r
a
t
e
n
o
r
m
a
l
a
n
d
m
a
l
i
c
io
u
s
.
T
h
e
g
r
a
p
h
i
c
a
l
u
s
e
r
i
n
t
e
r
f
a
c
e
m
e
t
h
o
d
s
h
o
w
s
d
i
a
g
r
a
m
m
a
t
i
c
al
l
y
a
n
d
t
e
x
t
u
a
l
l
y
t
h
e
d
a
t
a
o
f
c
a
p
t
u
r
e
d
a
n
d
c
a
t
e
g
o
r
i
z
e
d
p
a
c
k
e
t
s
.
H
o
w
e
v
e
r
,
t
h
i
s
m
e
c
h
a
n
i
s
m
p
r
o
v
i
d
es
l
e
s
s
p
r
e
c
is
i
o
n
r
a
t
e
a
n
d
i
n
c
r
ea
s
es
t
h
e
f
a
ls
e
p
o
s
i
t
i
v
e
r
at
e
a
n
d
f
a
ls
e
a
l
a
r
m
r
a
t
e
[
7
]
.
2.
RE
L
AT
E
D
WO
RK
S
T
h
e
clo
u
d
c
o
m
p
u
tin
g
s
y
s
tem
i
s
in
cr
ea
s
in
g
s
p
ee
d
ily
,
a
n
d
it
is
ap
p
r
o
p
r
iate
f
o
r
u
s
er
s
to
o
b
tai
n
s
er
v
ices
th
r
o
u
g
h
th
e
in
ter
n
et;
it
is
s
u
itab
le
f
o
r
ar
is
in
g
,
d
ep
lo
y
i
n
g
,
an
d
g
ettin
g
m
o
b
ile
ap
p
licatio
n
s
.
No
w,
s
ec
u
r
ity
is
a
n
ec
ess
ar
y
an
x
iety
d
u
e
to
th
e
o
p
en
an
d
d
is
s
em
in
ated
n
atu
r
e
o
f
th
e
clo
u
d
.
Nu
m
er
o
u
s
a
m
o
u
n
ts
o
f
d
ata
ar
e
ac
co
u
n
tab
le
f
o
r
ap
p
ea
lin
g
in
tr
u
s
io
n
[
8
]
.
I
DS
is
co
n
ce
n
tr
ated
o
n
b
o
o
s
tin
g
class
if
icatio
n
ac
c
u
r
ac
y
b
y
e
n
h
an
ci
n
g
th
e
f
ea
tu
r
e
s
elec
tio
n
an
d
co
n
s
id
er
in
g
th
e
en
s
em
b
le
an
d
th
e
cr
o
w
s
ea
r
ch
alg
o
r
ith
m
(
C
SA)
.
T
h
e
ch
o
ice
o
f
f
ea
tu
r
e
is
h
an
d
led
b
y
th
e
f
ilte
r
m
eth
o
d
to
r
e
ce
iv
e
th
e
f
ea
tu
r
e
s
ets.
T
h
e
en
s
em
b
le
m
eth
o
d
cr
ea
tes
th
e
weig
h
ts
with
th
e
C
SA
to
r
ec
eiv
e
th
e
b
est
o
u
tco
m
es.
Ho
wev
er
,
th
is
m
ec
h
an
is
m
r
aises
th
e
u
tili
za
tio
n
o
f
ca
lcu
latio
n
r
eso
u
r
ce
s
[
9
]
.
A
co
o
p
er
ativ
e
to
m
in
im
ize
th
e
co
llis
io
n
o
f
d
e
n
ial
o
f
s
er
v
ice
(
Do
S)
attac
k
s
i
n
clo
u
d
co
m
p
u
tin
g
.
I
t
ass
es
s
es
th
e
d
ep
en
d
ab
ilit
y
o
f
th
is
aler
t
m
es
s
ag
e
th
r
o
u
g
h
th
e
m
ajo
r
ity
v
o
te
m
eth
o
d
.
T
h
u
s
,
I
DSs
o
r
g
an
ized
in
clo
u
d
co
m
p
u
tin
g
r
eg
io
n
s
ex
cl
u
d
e
f
atalities;
o
n
e
co
u
l
d
av
o
i
d
Do
S a
ttack
s
[
1
0
]
.
Dete
ctin
g
an
o
m
alies
in
th
e
t
r
af
f
ic
o
n
a
n
etwo
r
k
e
n
tails
lo
o
k
in
g
f
o
r
p
atter
n
s
th
at
ar
e
o
u
t
o
f
th
e
o
r
d
in
ar
y
an
d
m
ig
h
t
p
o
in
t
to
p
o
ten
tial
v
u
ln
er
ab
ilit
ies.
T
h
e
m
eth
o
d
ca
n
f
u
n
ctio
n
b
y
class
if
y
in
g
n
etwo
r
k
d
ata
v
ia
a
co
llectio
n
o
f
d
ec
is
io
n
tr
ee
s
(
DT
)
,
wh
ic
h
in
tu
r
n
en
ab
les th
e
d
etec
tio
n
o
f
ab
er
r
an
t b
e
h
a
v
io
r
s
.
T
h
e
p
u
r
p
o
s
e
o
f
th
is
m
ec
h
an
is
m
is
to
b
etter
th
e
ac
cu
r
ac
y
an
d
ef
f
icien
cy
o
f
id
en
tify
in
g
ab
n
o
r
m
alities
with
in
n
etwo
r
k
tr
a
f
f
ic,
with
th
e
u
ltima
te
g
o
al
o
f
in
c
r
e
asin
g
o
v
e
r
all
n
etwo
r
k
s
ec
u
r
ity
[
1
1
]
.
Dete
ctio
n
o
f
a
n
o
m
alies
-
b
ased
in
tr
u
s
io
n
s
in
in
d
u
s
tr
ial
d
ata
u
s
in
g
s
u
p
p
o
r
t
v
ec
to
r
m
ac
h
in
e
(
SVM
)
an
d
r
an
d
o
m
f
o
r
ests
(
R
F).
T
h
e
p
r
o
ce
s
s
o
f
f
in
d
in
g
ab
n
o
r
m
al
p
atter
n
s
o
r
ac
tio
n
s
in
s
id
e
a
s
y
s
tem
is
wh
at
’
s
k
n
o
wn
as
an
o
m
aly
-
b
ased
in
tr
u
s
io
n
d
etec
tio
n
.
SVM
is
u
s
ed
b
ec
au
s
e
o
f
its
ca
p
ac
ity
to
class
if
y
d
ata
in
to
s
ev
er
al
clas
s
es,
d
if
f
er
en
tiatin
g
n
o
r
m
al
ac
tiv
ity
f
r
o
m
ab
e
r
r
an
t
b
eh
av
io
r
in
th
e
p
r
o
ce
s
s
.
On
th
e
o
th
er
h
an
d
,
R
Fs
m
ak
e
u
s
e
o
f
a
co
llectio
n
o
f
DT
to
class
if
y
d
ata,
wh
ich
in
cr
ea
s
es
p
r
ec
is
io
n
[
1
2
]
.
R
F
alg
o
r
ith
m
is
u
s
ed
to
id
en
tify
th
ese
ir
r
eg
u
lar
ities
an
d
ex
p
lain
th
e
id
en
tifie
d
ab
n
o
r
m
alities
.
T
h
e
tech
n
iq
u
e
en
ta
ils
lev
er
ag
in
g
th
e
R
F
m
o
d
el
n
o
t
ju
s
t
to
f
in
d
an
o
m
alies
b
u
t
also
to
g
i
v
e
r
elev
an
t
ex
p
lan
atio
n
s
o
r
in
s
ig
h
ts
in
to
wh
y
th
ese
an
o
m
alies
ar
o
s
e.
T
h
e
p
u
r
p
o
s
e
o
f
th
is
s
tu
d
y
is
to
im
p
r
o
v
e
th
e
in
ter
p
r
etab
ilit
y
o
f
an
o
m
aly
d
etec
tio
n
f
in
d
in
g
s
b
y
u
n
d
er
s
tan
d
in
g
th
e
d
ec
is
i
on
-
m
a
k
in
g
p
r
o
ce
s
s
o
f
th
e
R
F
alg
o
r
ith
m
[
1
3
]
.
T
h
e
e
x
p
lain
a
b
le
R
F
i
s
to
f
o
r
ec
ast
u
n
f
av
o
r
ab
le
o
cc
u
r
r
en
ce
s
o
r
ac
tiv
ities
k
n
o
wn
as
an
o
m
alies
ac
cu
r
ately
.
T
h
e
e
x
p
lain
ab
le
R
F
o
f
f
er
s
clea
r
an
d
u
n
d
er
s
ta
n
d
ab
le
in
s
ig
h
ts
in
to
th
e
s
tu
d
y
’
s
d
ec
is
io
n
-
m
a
k
in
g
p
r
o
ce
s
s
.
T
h
e
p
u
r
p
o
s
e
o
f
ad
o
p
tin
g
th
is
m
o
d
el
is
to
id
en
tif
y
an
o
m
alies
b
u
t
also
p
r
o
v
id
e
c
o
n
cise
ex
p
lan
atio
n
s
.
T
h
is
s
tr
ateg
y
im
p
r
o
v
es
th
e
in
t
er
p
r
etab
ilit
y
o
f
th
e
f
in
d
in
g
s
o
f
an
o
m
al
y
d
etec
tio
n
,
allo
win
g
o
n
e
to
co
m
p
r
e
h
en
d
b
etter
th
e
f
ac
to
r
s
th
at
led
to
t
h
e
d
is
co
v
er
y
o
f
p
r
o
b
lem
s
an
d
to
d
ev
is
e
s
u
itab
le
s
o
lu
tio
n
s
to
av
er
t
u
n
f
av
o
r
ab
le
o
cc
u
r
r
e
n
ce
s
,
lead
in
g
to
an
in
c
r
ea
s
e
in
b
o
th
p
r
o
d
u
ctiv
ity
an
d
s
ec
u
r
ity
[
1
4
]
.
W
h
e
n
c
a
r
r
y
i
n
g
o
u
t
l
o
c
a
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li
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b
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HC
)
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o
v
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f
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t
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u
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a
(
t
h
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n
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g
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b
o
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h
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o
d
)
[
1
5
]
.
I
f
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ti
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h
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r
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am
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f
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te
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l
i
t
y
w
il
l
b
e
p
r
e
s
e
n
t
e
d
in
H
C
[
1
6
]
.
I
t
a
c
t
s
a
s
a
g
u
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d
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t
o
t
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q
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
7
,
No
.
1
,
J
an
u
ar
y
20
2
5
:
1
34
-
1
42
136
Fire
walls
ex
am
in
e
th
e
co
n
tr
o
l r
u
les,
an
d
b
ased
o
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a
p
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k
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itted
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ef
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.
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ac
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to
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tr
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r
tain
cr
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ia.
Fo
r
a
f
ir
ewa
ll
to
v
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if
y
t
h
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r
u
les,
it
ju
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C
P/IP
p
r
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to
co
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wh
ich
m
ay
b
e
FTP,
HT
T
P,
o
r
T
eln
et
[
1
7
]
.
On
th
e
o
th
e
r
h
an
d
,
it
d
o
es
n
o
t
ex
am
in
e
th
e
in
f
o
r
m
atio
n
in
clu
d
ed
in
th
e
n
etwo
r
k
p
ac
k
et.
As
lo
n
g
a
s
th
e
h
ea
d
er
o
f
th
e
p
ac
k
et
co
m
p
lies
wi
th
th
e
r
u
les
th
at
h
av
e
b
ee
n
s
et
u
p
in
th
e
f
ir
ewa
ll,
it
wo
n
’
t
m
atter
wh
et
h
er
th
e
d
ata
co
m
p
r
is
es
h
ar
m
f
u
l
co
d
e
o
r
n
o
t;
t
h
e
f
ir
ewa
ll
wi
ll
s
till
let
th
e
p
ac
k
et
g
o
th
r
o
u
g
h
.
C
o
n
s
eq
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e
n
tly
,
d
es
p
ite
a
f
ir
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ll,
an
attac
k
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o
u
r
tr
u
s
ted
n
etwo
r
k
is
s
till
p
o
s
s
ib
le
[
1
8
].
I
DS
is
s
ig
n
if
ican
t
f
o
r
d
etec
ti
n
g
a
n
a
n
o
m
aly
in
clo
u
d
c
o
m
p
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tin
g
th
at
ca
n
b
e
r
ec
o
g
n
ized
as
s
ev
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al
attac
k
s
with
f
ewe
r
f
alse
p
o
s
itiv
es.
An
ef
f
ec
tiv
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I
DS
ap
p
ly
in
g
an
en
s
em
b
le
-
b
ased
lear
n
in
g
m
eth
o
d
u
s
es
class
if
ier
s
an
d
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v
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m
eth
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d
.
T
h
is
d
etec
ts
th
e
in
t
r
u
s
io
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e
f
f
icien
tly
.
Ho
wev
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r
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it
r
aises
th
e
r
eq
u
i
r
ed
tim
e
f
o
r
ex
ec
u
tio
n
[
1
9
]
.
Featu
r
e
Selec
tio
n
an
d
i
n
tr
u
s
io
n
f
o
r
ec
asti
n
g
to
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alu
ate
its
ef
f
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tiv
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n
ess
.
T
h
e
c
o
o
p
e
r
ativ
e
f
ea
tu
r
e
s
elec
tio
n
m
eth
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d
in
c
o
r
p
o
r
ates
tim
e
s
er
ies
an
aly
s
is
to
r
ec
o
g
n
ize
a
n
o
m
alies
[
2
0
]
.
An
ef
f
icien
t
I
DS
ap
p
lies
an
en
s
em
b
le
f
ea
tu
r
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o
f
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ized
f
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ets.
T
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s
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asts
th
e
n
etwo
r
k
tr
af
f
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b
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h
av
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[
2
1
]
.
I
n
d
ian
Sig
n
L
an
g
u
ag
e
(
I
SL)
is
th
e
p
r
in
cip
al
ty
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e
o
f
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m
m
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f
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m
o
s
t
d
u
m
b
an
d
d
ea
f
citizen
s
n
atio
n
wid
e
[
2
2
]
.
I
t
is
a
d
ev
elo
p
ed
n
at
u
r
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lan
g
u
ag
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th
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as
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s
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s
s
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tax
.
T
r
an
s
latio
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s
y
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tem
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tia
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to
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m
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m
m
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ity
o
f
d
ea
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d
h
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of
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le.
T
o
f
ac
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e
two
-
way
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m
m
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n
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n
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ter
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ac
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r
ch
itectu
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p
ab
le
o
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f
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ec
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y
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f
I
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n
als.
W
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s
u
itab
le
f
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s
u
ch
ap
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licatio
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u
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to
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en
s
in
g
,
to
le
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ce
to
h
o
s
tile
co
n
d
i
tio
n
s
,
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d
lo
w
p
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co
n
s
u
m
p
tio
n
.
T
h
e
r
esear
ch
p
r
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v
id
es
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n
iq
u
e
W
SN
d
ep
lo
y
m
en
t,
d
ata
ag
g
r
eg
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n
,
an
d
r
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r
ce
o
p
tim
izatio
n
m
eth
o
d
o
lo
g
ies
f
o
r
d
is
aster
m
a
n
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g
e
m
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n
t
.
T
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n
g
e
v
i
t
y
.
T
h
e
r
es
e
a
r
ch
a
l
s
o
e
x
a
m
i
n
e
s
t
h
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y
n
c
h
r
o
n
i
za
t
i
o
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o
f
A
I
a
n
d
h
u
m
a
n
b
r
a
i
n
p
o
w
e
r
c
a
l
c
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l
at
i
o
n
s
w
i
t
h
W
SN
s
t
o
e
n
a
b
l
e
s
m
a
r
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n
a
v
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g
a
t
i
o
n
a
n
d
r
o
b
o
t
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z
e
d
c
r
i
s
is
r
e
s
p
o
n
s
e
.
T
h
e
r
es
e
a
r
c
h
s
t
u
d
y
a
d
d
r
e
s
s
es
W
S
N
s
e
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u
r
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t
y
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d
p
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y
i
n
d
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a
s
t
e
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m
a
n
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g
e
m
e
n
t
.
I
t
i
d
e
n
t
i
f
i
es
f
l
aws
a
n
d
s
u
g
g
es
ts
w
a
y
s
t
o
cl
a
s
s
i
f
y
,
v
e
r
i
f
y
,
a
n
d
s
h
a
r
e
d
at
a
.
A
r
e
e
n
a
c
t
e
d
f
i
as
c
o
is
u
s
e
d
t
o
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v
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l
u
a
t
e
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h
e
p
r
o
p
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s
e
d
a
l
te
r
n
a
t
i
v
e
s
.
S
i
t
u
at
i
o
n
a
l
aw
a
r
e
n
es
s
,
r
e
s
p
o
n
s
e
c
o
o
r
d
i
n
a
ti
o
n
,
a
n
d
e
m
e
r
g
e
n
c
y
o
p
e
r
a
t
i
o
n
s
e
f
f
i
c
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e
n
c
y
i
n
c
r
e
as
e
w
it
h
t
h
e
p
r
o
v
i
d
e
d
t
e
c
h
n
i
q
u
e
s
[
2
3
]
.
P
o
w
e
r
q
u
a
l
i
t
y
m
o
n
i
t
o
r
i
n
g
o
f
f
e
r
s
f
o
r
e
c
a
s
t
e
d
i
n
s
i
g
h
ts
i
n
t
o
p
o
w
e
r
q
u
a
l
i
t
y
f
l
u
ct
u
a
t
i
o
n
s
v
i
a
e
x
a
m
i
n
i
n
g
p
a
s
t
d
a
t
a
a
n
d
p
at
t
e
r
n
s
t
h
a
t
e
n
h
a
n
c
e
s
g
r
i
d
s
t
a
b
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it
y
a
s
w
el
l
a
s
al
l
o
c
at
i
o
n
o
f
r
e
s
o
u
r
c
e
s
[
2
4
]
.
T
h
e
s
y
s
t
e
m
u
s
e
s
i
n
t
e
r
n
e
t
o
f
t
h
i
n
g
s
(
I
o
T
)
s
e
n
s
o
r
s
a
n
d
c
a
m
e
r
as
p
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s
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t
i
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n
ed
i
n
p
a
r
k
i
n
g
l
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t
s
t
o
t
r
a
c
k
t
h
e
o
c
c
u
p
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y
s
t
a
t
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s
o
f
s
p
e
c
i
f
i
c
p
a
r
k
i
n
g
s
p
o
t
s
i
n
r
e
a
l
-
t
im
e
.
T
h
e
a
c
q
u
i
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d
d
a
t
a
i
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e
n
t
to
a
c
l
o
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d
s
e
r
v
e
r
f
o
r
a
n
a
l
y
s
is
a
n
d
p
r
o
c
es
s
i
n
g
.
T
h
e
co
n
v
o
l
u
t
i
o
n
a
l
n
e
u
r
a
l
n
et
w
o
r
k
(
C
N
N
)
a
l
g
o
r
i
t
h
m
,
a
d
e
e
p
l
e
a
r
n
in
g
a
p
p
r
o
a
c
h
,
i
s
u
s
e
d
t
o
e
v
a
l
u
a
t
e
t
h
e
c
a
m
e
r
a
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m
a
g
es
a
n
d
a
c
c
u
r
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t
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l
y
d
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t
e
r
m
i
n
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f
p
a
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g
s
p
o
t
s
a
r
e
o
c
c
u
p
ie
d
[
2
5
]
.
3.
P
RO
P
O
SE
D
M
E
T
H
O
D
T
h
e
d
ata
p
r
e
-
p
r
o
ce
s
s
in
g
p
r
o
c
ed
u
r
e
is
u
s
ed
t
o
ar
r
a
n
g
e
t
h
e
m
f
o
r
s
elec
tin
g
th
e
f
ea
t
u
r
e.
T
h
e
tr
ain
in
g
d
ataset
co
n
tain
s
b
in
ar
y
,
s
y
m
b
o
lic,
an
d
n
u
m
er
ical
d
ata
.
T
h
is
p
r
o
ce
d
u
r
e
ta
k
es
clea
n
as
well
as
n
u
m
er
ic
in
p
u
ts
,
s
o
th
e
d
ataset
s
h
o
u
ld
b
e
o
r
g
a
n
ized
f
ir
s
t.
T
h
e
Fig
u
r
e
1
s
tep
s
o
p
er
ate
th
e
b
lo
ck
d
iag
r
am
o
f
th
e
R
FH
C
s
ch
em
e
an
d
th
ese
co
m
p
o
n
e
n
ts
.
3
.
1
.
P
re
pro
ce
s
s
ing
T
ak
in
g
o
u
t
im
p
er
f
ec
t
o
u
tlier
s
u
n
r
elate
d
,
r
e
p
lica
v
alu
es
an
d
ca
n
ce
lin
g
f
ea
t
u
r
es:
i
n
th
e
d
ataset,
we
d
r
o
p
p
ed
f
ea
tu
r
es,
f
o
r
ex
am
p
le
,
th
e
I
P
a
d
d
r
ess
o
f
th
e
s
en
d
er
an
d
r
ec
eiv
er
.
I
n
ad
d
itio
n
,
th
e
a
d
d
r
ess
o
f
s
en
d
er
an
d
r
ec
eiv
er
,
tim
estam
p
an
d
s
en
d
er
Po
r
t,
an
d
o
th
er
f
ea
t
u
r
es
ar
e
r
em
o
v
ed
.
Featu
r
e
m
ap
p
in
g
:
r
ep
r
esen
ts
th
e
tr
an
s
latin
g
o
f
th
e
ca
te
g
o
r
ical
v
ar
iab
les
in
to
ar
ith
m
etica
l
f
o
r
m
.
On
e
-
h
o
t
e
n
co
d
in
g
g
iv
es
a
s
u
p
er
io
r
class
if
ier
ex
ec
u
tio
n
.
T
h
e
s
ca
lin
g
o
f
a
f
ea
tu
r
e
is
ca
lled
d
ata
n
o
r
m
al
izatio
n
,
co
n
v
er
tin
g
en
tire
v
al
u
es
f
r
o
m
a
s
et
o
f
f
ea
tu
r
es
in
to
a
r
an
g
e
o
f
p
r
e
s
ets.
Stan
d
ar
d
izatio
n
is
k
n
o
wn
as
a
Z
-
s
co
r
e
n
o
r
m
aliza
tio
n
.
No
r
m
aliza
tio
n
(
m
in
-
m
ax
)
is
th
e
p
r
o
ce
d
u
r
e
o
f
ch
an
g
i
n
g
as
well
as
r
esizin
g
v
alu
es,
wh
ich
d
r
o
p
in
t
h
e
s
er
i
es
[
0
,
1
]
.
T
h
e
m
in
-
m
ax
s
ca
lin
g
eq
u
atio
n
is
d
ef
in
e
d
in
(
1
)
.
∗
=
(
−
)
(
−
)
(
1
)
Her
e,
k
is
th
e
p
r
elim
in
a
r
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v
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lu
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k
*
r
ep
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th
e
d
ata
f
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llo
win
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d
ev
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o
p
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en
t,
min
d
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n
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af
f
ec
tin
g
d
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s
eq
u
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’
s
s
m
allest v
alu
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an
d
max
in
d
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th
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h
ig
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es
t v
alu
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T
h
e
in
f
o
r
m
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n
ee
d
ed
to
c
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llect
in
th
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class
f
ield
is
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in
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i
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T
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f
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,
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class
co
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m
n
h
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p
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in
to
two
d
is
tin
ct
g
r
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p
s
:
n
o
r
m
al
an
d
ab
er
r
an
t.
C
o
n
ce
r
n
in
g
th
e
ca
teg
o
r
izatio
n
o
f
attac
k
s
,
th
e
class
co
lu
m
n
is
s
u
b
d
iv
i
d
ed
in
to
t
h
e
f
o
llo
win
g
ca
teg
o
r
ies:
k
n
o
wn
an
d
u
n
k
n
o
w
n
attac
k
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
R
a
n
d
o
m
f
o
r
est a
lg
o
r
ith
m
w
ith
h
ill climb
in
g
a
lg
o
r
ith
m
to
imp
r
o
ve
…
(
S
a
th
ee
s
h
K
u
ma
r
S
ek
a
r
)
137
Fig
u
r
e
1
.
B
lo
ck
d
iag
r
am
o
f
th
e
R
FH
C
s
ch
em
e
3
.
2
.
F
e
a
t
ure
s
elec
t
io
n
I
t
r
ep
r
esen
ts
a
p
r
e
-
p
r
o
ce
s
s
in
g
m
eth
o
d
th
at
ass
is
ts
in
s
elec
t
in
g
ap
p
r
o
p
r
iate
f
ea
tu
r
es.
I
t
r
e
d
u
ce
s
th
e
d
im
en
s
io
n
ality
o
f
d
ata
b
y
m
in
im
izin
g
u
n
n
ec
ess
ar
y
an
d
u
n
r
elate
d
attr
ib
u
tes.
W
h
ile
ir
r
el
ev
an
t
f
ea
tu
r
es
ar
e
ap
p
en
d
e
d
to
th
e
class
if
icati
o
n
p
r
o
ce
d
u
r
e
,
r
ed
u
cin
g
ac
c
u
r
ac
y
,
it
r
eq
u
ir
es
m
o
r
e
s
p
ac
e
an
d
tim
e.
T
h
u
s
,
th
e
f
ea
tu
r
e
s
elec
tio
n
is
v
ital
b
ec
au
s
e
it
is
ap
p
r
o
p
r
iate
f
o
r
a
d
ee
p
er
r
ea
lizatio
n
o
f
d
ata
b
y
h
o
ld
in
g
i
m
p
er
ativ
e
s
u
itab
le
f
ea
tu
r
es,
th
u
s
en
h
an
c
in
g
th
e
class
if
ier
’
s
ac
cu
r
ac
y
,
s
p
ee
d
,
an
d
f
o
r
ec
asti
n
g
ca
p
ac
ity
.
T
h
is
m
ec
h
an
is
m
u
tili
ze
s
an
HC
-
b
ased
f
ea
tu
r
e
s
elec
tio
n
th
at
s
h
o
r
tlis
ts
im
p
o
r
ta
n
t a
ttrib
u
tes.
T
h
e
b
est
-
r
ec
eiv
ed
r
esu
lt
is
n
ex
t
p
ass
ed
to
th
e
HC
to
s
p
e
ed
u
p
th
e
s
ea
r
ch
a
n
d
d
ef
ea
t
th
e
s
lo
w
co
n
v
er
g
en
ce
tech
n
iq
u
e.
HC
i
s
an
iter
ativ
e
tech
n
iq
u
e
th
at
i
n
itiates
with
a
r
an
d
o
m
r
eso
lu
tio
n
to
a
d
if
f
icu
lty
.
Nex
t,
tr
ies
to
d
ec
id
e
o
n
a
b
etter
r
eso
lu
tio
n
b
y
in
c
r
em
en
t
ally
s
h
if
tin
g
a
p
ar
ticu
lar
r
es
o
lu
tio
n
co
m
p
o
n
e
n
t.
W
h
en
th
e
a
d
ap
tatio
n
b
u
ild
s
th
e
b
est
s
o
lu
tio
n
,
th
e
ad
d
itiv
e
u
p
d
ate
is
f
u
lf
illed
o
n
th
e
r
ec
en
t
s
o
lu
tio
n
,
wh
ich
is
r
ep
ea
ted
till
n
o
e
x
tr
a
en
h
an
ce
m
en
ts
ca
n
b
e
estab
lis
h
ed
.
3
.
3
.
Co
rr
el
a
t
io
n o
f
f
ea
t
ure
I
t
is
a
v
alu
ab
le
m
eth
o
d
f
o
r
f
ea
tu
r
e
en
g
i
n
ee
r
in
g
,
as
well
as
it
is
a
n
u
m
er
ical
p
r
o
ce
s
s
th
at
s
p
ec
if
ies
th
e
s
ig
n
if
ican
ce
am
o
n
g
s
t
o
n
e
o
r
m
o
r
e
v
ar
iab
les
to
n
o
tice
t
h
e
i
n
ter
r
elate
d
v
ital
f
ea
tu
r
es.
Ne
x
t,
th
e
p
r
e
-
p
r
o
ce
s
s
ed
d
ata
is
s
p
lit
in
to
two
ty
p
es,
s
u
ch
as
tr
ain
in
g
as
well
as
test
d
ataset.
I
n
th
e
tr
ain
in
g
d
ataset,
r
em
o
v
e
th
e
f
ea
tu
r
es
an
d
cr
ea
te
th
e
d
if
f
er
e
n
t c
lass
if
icatio
n
s
in
th
e
test
d
ataset
.
3
.
4
.
RF
-
ba
s
ed
intr
us
io
n det
ec
t
io
n
Af
ter
th
e
f
ea
tu
r
e
s
elec
tio
n
p
r
o
ce
s
s
,
th
is
m
ec
h
an
is
m
u
s
es
a
n
R
F
class
if
ier
alg
o
r
ith
m
tr
a
in
e
d
with
t
h
e
two
f
ea
tu
r
es
p
ick
ed
o
u
t
f
r
o
m
a
s
u
b
s
et
o
f
th
e
d
ataset
to
r
ec
o
g
n
ize
in
tr
u
s
io
n
s
.
T
h
e
R
F
alg
o
r
ith
m
co
n
ce
n
tr
ated
o
n
r
ec
eiv
in
g
r
eliab
le
f
o
r
ec
asti
n
g
.
T
h
e
p
r
o
p
o
s
ed
m
eth
o
d
-
b
as
ed
I
DS
c
o
n
tain
s
s
elec
tin
g
f
ea
tu
r
es
to
r
ec
o
g
n
ize
an
d
m
er
g
e
v
alu
ab
le
f
ea
tu
r
es
f
o
r
p
r
ec
is
e
id
en
tific
atio
n
.
On
ce
th
e
f
ea
tu
r
e
s
u
b
s
et
is
p
ick
e
d
o
u
t,
th
e
R
F
class
if
ier
d
if
f
er
en
tiates
b
etwe
en
an
ac
t
iv
ity
o
f
r
ea
l
o
r
in
tr
u
s
io
n
.
T
h
e
R
F
clas
s
if
ier
clu
s
ter
s
s
ev
er
al
DT
,
an
d
th
o
s
e
o
u
tco
m
es
ar
e
j
o
in
ed
in
t
o
o
n
e
f
in
al
o
u
t
p
u
t.
T
h
is
DT
alg
o
r
i
th
m
p
er
f
o
r
m
s
class
if
icatio
n
a
n
d
r
eg
r
ess
io
n
.
R
F
alg
o
r
ith
m
ev
a
d
es th
e
o
v
er
-
ad
j
u
s
tm
en
t iss
u
e
.
B
ase
clas
s
if
ier
s
u
s
e
an
m
tr
ee
ar
r
an
g
em
e
n
t
{h
(
X,
δk
)
,
k
=
1
,
2
.
.
m
}
.
Her
e,
X
in
d
icate
s
th
e
in
p
u
t
d
ata,
an
d
δ
d
ep
icts
th
e
d
ep
en
d
en
t
d
is
tr
ib
u
ted
r
a
n
d
o
m
v
ec
to
r
.
E
a
ch
DT
p
ic
k
s
o
u
t
d
ata
ar
b
itra
r
ily
f
r
o
m
th
e
u
s
ab
le
d
ata.
C
o
n
s
tr
u
ct
a
f
o
r
est
to
ass
em
b
le
th
e
am
o
u
n
t
o
f
tr
ee
s
k
v
i
a
r
eiter
atin
g
th
e
s
tep
s
g
r
ea
ter
t
h
an
f
o
r
th
e
am
o
u
n
t
o
f
tim
es k
.
I
n
tr
ain
in
g
d
ata,
th
e
R
F
alg
o
r
ith
m
p
r
o
v
id
es
less
s
en
s
i
tiv
ity
to
o
u
tlier
d
ata
b
ec
au
s
e
o
f
its
ab
ilit
y
to
co
n
q
u
e
r
th
e
is
s
u
e
o
f
o
v
er
f
itti
n
g
.
I
t
is
ea
s
y
to
lau
n
ch
p
ar
a
m
eter
s
th
at
ev
ad
e
th
e
n
ec
ess
i
ty
f
o
r
tr
ee
tr
im
m
in
g
.
T
h
e
R
F
alg
o
r
ith
m
ad
m
its
an
ass
em
b
ly
o
f
tr
ee
-
s
tr
u
ctu
r
ed
le
ar
n
er
s
,
wh
ich
ev
er
y
ca
s
t
a
m
ajo
r
ch
o
ice
f
o
r
th
e
class
with
th
e
m
o
s
t
in
p
u
t.
I
t
is
s
el
f
-
g
o
v
e
r
n
in
g
o
f
p
r
io
r
r
an
d
o
m
v
ec
to
r
s
o
f
th
e
s
am
e
d
is
tr
ib
u
tio
n
,
a
n
d
an
u
p
p
e
r
b
o
u
n
d
is
d
er
iv
ativ
e
f
o
r
R
F to
o
b
tain
th
e
f
o
r
ec
asti
n
g
er
r
o
r
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
7
,
No
.
1
,
J
an
u
ar
y
20
2
5
:
1
34
-
1
42
138
4.
E
XP
E
R
I
M
E
N
T
A
L
ANA
L
Y
SI
S
E
x
p
er
im
en
tal
an
aly
s
es
ar
e
p
e
r
f
o
r
m
e
d
o
n
t
h
e
NSL
-
KDD
d
a
tasets
.
W
e
co
n
ce
n
tr
ate
o
n
cla
s
s
if
icatio
n
m
o
d
els,
an
d
m
o
r
e
s
p
ec
if
ically
b
in
a
r
y
class
if
icatio
n
,
s
in
ce
I
DS,
m
a
y
b
ec
o
m
e
p
r
o
b
lem
atic
wh
ile
u
tili
zin
g
lab
eled
d
ata
to
tr
y
t
o
d
eter
m
i
n
e
wh
eth
er
o
r
n
o
t
a
n
item
is
a
m
em
b
er
o
f
t
h
e
in
tr
u
s
io
n
cla
s
s
[
2
6
]
.
T
h
e
r
esu
lts
r
etu
r
n
ed
b
y
an
alg
o
r
ith
m
f
o
r
b
in
ar
y
class
if
icatio
n
ar
e
eith
er
0
o
r
1
.
T
h
er
ef
o
r
e,
s
elec
tin
g
th
e
ap
p
r
o
p
r
iate
m
ea
s
u
r
e
is
ess
en
tia
l
f
o
r
an
aly
zin
g
an
d
v
er
i
f
y
in
g
th
e
R
F
alg
o
r
ith
m
.
W
h
en
d
ea
lin
g
with
is
s
u
es
o
f
th
is
k
in
d
,
th
e
m
etr
ics
o
f
ten
in
cl
u
d
e
c
o
m
p
ar
in
g
th
e
ac
t
u
al
class
es
an
d
th
e
m
o
d
els
’
f
o
r
ec
asts
.
T
h
is
en
ab
les
th
e
esti
m
ated
p
r
o
b
a
b
ilit
y
f
o
r
th
ese
class
es
to
b
e
in
ter
p
r
eted
m
ea
n
i
n
g
f
u
lly
.
W
e
ar
e
ab
le
to
co
n
s
tr
u
ct
m
etr
ics
s
u
ch
as
ac
cu
r
ac
y
,
r
ec
all,
an
d
p
r
e
cisi
o
n
b
ased
o
n
th
is
m
ec
h
an
is
m
,
w
h
ich
will
en
a
b
le
u
s
to
is
o
late
in
f
iltra
tio
n
u
s
in
g
th
e
R
F m
eth
o
d
[
2
7
]
.
T
h
ese
m
etr
ics
will
h
elp
u
s
to
d
eter
m
in
e
wh
eth
er
o
r
n
o
t
an
ev
en
t
o
cc
u
r
r
e
d
.
I
t
co
n
s
is
ts
o
f
th
e
f
o
llo
win
g
f
o
u
r
v
ar
ia
b
les:
tr
u
e
p
o
s
itiv
e
(
T
P),
tr
u
e
n
eg
ativ
e
(
T
R
N)
,
f
alse
p
o
s
itiv
e
(
FAP),
an
d
f
alse
n
e
g
ativ
e
(
FAN)
.
W
h
en
ev
alu
atin
g
th
e
ef
f
ec
tiv
en
ess
o
f
a
m
o
d
el
,
ea
ch
v
ar
iab
le
d
en
o
tes
a
d
is
tin
ct
m
ea
n
in
g
th
at
is
tak
en
in
to
ac
co
u
n
t.
Fo
r
ex
am
p
le,
T
R
P
s
u
g
g
ests
th
at
th
e
ex
is
ten
ce
o
f
d
an
g
er
s
was
ac
cu
r
ately
id
en
t
if
ied
.
On
t
h
e
o
th
e
r
h
an
d
,
T
R
N
in
d
icate
s
th
at
th
e
lack
o
f
th
r
ea
ts
was
ac
cu
r
ately
f
o
r
ec
asted
,
wh
ich
is
a
p
o
s
itiv
e
d
ev
elo
p
m
en
t.
T
h
e
f
ac
t
th
at
th
e
m
o
d
el
in
co
r
r
ec
tly
p
r
ed
icted
t
h
at
th
er
e
w
as
n
o
d
an
g
er
(
FAN)
an
d
f
ail
ed
to
id
en
tify
th
e
ex
is
ten
ce
o
f
th
e
t
h
r
ea
t
(
FAP)
s
u
g
g
ests
th
at
t
h
e
m
o
d
el
d
id
n
o
t
ad
e
q
u
ately
d
etec
t
t
h
e
p
r
e
s
en
ce
o
f
th
e
t
h
r
ea
t
.
Acc
u
r
ac
y
(
AC
C
)
r
ep
r
esen
ts
th
e
p
er
ce
n
tag
e
o
f
p
r
ec
is
e
p
r
ed
ictio
n
s
b
u
ilt
in
r
elatio
n
to
all
ca
s
es.
AC
C
co
m
p
u
tatio
n
is
s
p
ec
if
ied
in
(
2
)
.
R
ec
all
m
etr
ic
is
ap
p
lie
d
to
d
ec
id
e
th
e
p
er
ce
n
ta
g
e
o
f
s
u
itab
ly
class
if
ied
p
o
s
itiv
e
p
atter
n
s
.
T
h
is
ca
lcu
latio
n
is
s
p
ec
if
ied
in
(
3
)
.
Pre
cisi
o
n
r
ep
r
esen
ts
th
e
ex
p
ec
ted
p
at
ter
n
s
,
an
d
it
co
u
n
ts
th
e
am
o
u
n
t
o
f
p
r
ec
is
ely
f
o
r
ec
asted
p
o
s
itiv
e
p
atter
n
s
in
a
p
o
s
itiv
e
class
.
T
h
is
ca
lcu
latio
n
is
s
p
ec
if
ied
in
(
4
)
.
Fig
u
r
e
2
ex
p
lain
s
ANND
an
d
DDHC a
p
p
r
o
ac
h
es f
o
r
f
alse p
o
s
itiv
e
r
atio
b
ased
o
n
e
x
p
e
r
im
en
t c
o
u
n
t
.
=
+
+
+
+
(
2
)
=
+
(
3
)
=
+
(
4
)
Fro
m
Fig
u
r
e
2
,
th
e
p
r
o
p
o
s
ed
R
FHC
m
ec
h
an
is
m
u
s
es
th
e
R
F
alg
o
r
ith
m
to
d
etec
t
t
h
e
in
tr
u
s
io
n
ef
f
icien
tly
.
Fu
r
th
er
m
o
r
e,
it
u
s
es
th
e
h
ill
clim
b
in
g
tec
h
n
iq
u
e
to
s
elec
t
th
e
f
ea
tu
r
es
wel
l.
C
o
n
v
er
s
ely
,
th
e
ex
is
tin
g
m
ec
h
an
is
m
DL
I
D
in
cr
ea
s
es
th
e
m
is
s
d
etec
tio
n
r
atio
s
in
ce
it
is
n
o
t
p
er
f
o
r
m
e
d
d
u
r
in
g
th
e
n
etwo
r
k
in
tr
u
s
io
n
.
Fig
u
r
e
3
ex
p
lain
s
Do
S I
n
tr
u
s
io
n
d
etec
tio
n
r
atio
f
o
r
R
FHC
an
d
DL
I
D
m
ec
h
an
is
m
s
.
Fig
u
r
e
2
.
DL
I
D
a
n
d
R
FHC
ap
p
r
o
ac
h
f
o
r
m
is
s
in
tr
u
s
io
n
d
ete
ctio
n
r
atio
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
R
a
n
d
o
m
f
o
r
est a
lg
o
r
ith
m
w
ith
h
ill climb
in
g
a
lg
o
r
ith
m
to
imp
r
o
ve
…
(
S
a
th
ee
s
h
K
u
ma
r
S
ek
a
r
)
139
Fig
u
r
e
3
.
R
FHC
an
d
DL
I
D
m
e
ch
an
is
m
s
f
o
r
Do
S
i
n
tr
u
s
io
n
d
e
tectio
n
r
atio
Gen
er
ally
,
th
e
in
tr
u
s
io
n
d
ete
ctio
n
r
atio
is
m
in
im
ized
b
y
r
aisi
n
g
th
e
in
tr
u
s
i
o
n
co
u
n
t.
Ho
wev
er
,
th
e
p
r
o
p
o
s
ed
R
FHC
m
ec
h
an
is
m
in
cr
ea
s
es
th
e
d
etec
tio
n
r
at
io
s
in
ce
it
ap
p
lies
an
R
F
alg
o
r
ith
m
to
d
etec
t
th
e
in
tr
u
s
io
n
ef
f
icien
tly
.
T
h
e
ex
is
tin
g
DL
I
D
m
ec
h
an
is
m
p
r
o
v
id
es
a
less
er
d
etec
tio
n
r
ati
o
th
an
an
R
FHC
m
ec
h
an
is
m
.
I
n
a
d
d
itio
n
,
t
h
e
DL
I
D
m
ec
h
an
is
m
d
o
es
n
o
t
u
s
e
th
e
o
p
tim
al
s
ea
r
ch
alg
o
r
ith
m
,
b
u
t
th
e
p
r
o
p
o
s
ed
m
ec
h
an
is
m
u
s
es th
e
h
ill clim
b
in
g
m
eth
o
d
to
s
elec
t th
e
b
est f
ea
tu
r
e
.
Alter
n
ativ
ely
,
to
en
s
u
r
e
th
e
e
f
f
icien
cy
o
f
t
h
e
m
o
d
el,
t
h
e
R
FHC
m
ec
h
an
is
m
is
em
p
lo
y
ed
.
Fig
u
r
e
4
d
is
p
lay
s
th
e
r
esu
lts
,
l
ik
e
p
r
ec
is
io
n
,
r
ec
all,
an
d
ac
cu
r
ac
y
o
f
R
FHC
an
d
DL
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ith
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CO
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Dete
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ith
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a
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d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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5
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52
In
d
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n
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J
E
lec
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n
g
&
C
o
m
p
Sci
,
Vo
l.
3
7
,
No
.
1
,
J
an
u
ar
y
20
2
5
:
1
34
-
1
42
140
n
etwo
r
k
f
o
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d
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tin
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tr
u
s
io
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.
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h
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o
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m
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tio
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elate
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ata
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ase.
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ith
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ates
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tio
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a
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d
d
im
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n
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ed
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e
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is
s
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etec
tio
n
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Ad
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,
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e,
we
will
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ly
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g
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d
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t
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u
ltip
le
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s
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d
eq
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ate
th
e
clo
u
d
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y
s
tem
lo
ad
.
RE
F
E
R
E
NC
E
S
[
1
]
M
.
G
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.
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.
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.
J.
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3
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.
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,
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V
.
C
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[
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A
.
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me
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M
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f
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En
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p
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&
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p
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:
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ma
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[
6
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A
.
K
h
r
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sa
t
,
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.
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o
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l
,
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.
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mp
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d
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K
a
mr
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a
ma
n
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:
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s,
d
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d
c
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.
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.
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.
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8
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P
.
R
a
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a
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.
,
“
I
n
t
r
u
si
o
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d
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t
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c
t
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n
sy
st
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ms
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p
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d
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m
:
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y
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s
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2
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[
9
]
M
.
B
a
k
r
o
e
t
a
l
.
,
“
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f
i
c
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mb
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El
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)
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[
1
0
]
C.
-
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.
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.
C
.
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lan
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m
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r
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g
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se
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g
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tri
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v
a
l
(CB
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a
n
d
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a
c
h
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rn
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g
.
S
h
e
c
a
n
b
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c
o
n
tac
t
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t
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m
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il
:
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p
in
jar
k
a
r@sitn
a
g
p
u
r.
si
u
.
e
d
u
.
i
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
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52
In
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142
Dr
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t
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h
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t
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il
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Ma
n
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rk
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s
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n
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h
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r
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telli
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e
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lea
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n
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ima
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ro
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re
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it
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e
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s
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sh
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d
m
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n
y
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se
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rc
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rti
c
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in
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ll
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p
u
ted
j
o
u
r
n
a
ls
a
n
d
fil
e
d
P
a
ten
ts als
o
.
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c
a
n
b
e
c
o
n
t
a
c
t
a
t
e
m
a
il
:
sa
th
ish
m
@c
it
c
h
e
n
n
a
i.
n
e
t.
Dr
.
Mu
n
n
a
n
g
i
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o
ti
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d
d
y
re
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d
th
e
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h
.
D.
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g
re
e
i
n
ECE
fro
m
KU
,
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ip
u
r
in
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n
u
a
r
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2
0
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9
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n
d
t
h
e
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.
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h
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d
e
g
re
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i
n
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sig
n
fr
o
m
th
e
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a
n
a
n
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iv
e
rsity
,
AP,
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d
ia,
in
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0
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n
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t
h
e
B.
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h
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d
e
g
re
e
in
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e
c
tr
o
n
ics
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n
d
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o
m
m
u
n
ica
ti
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n
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g
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n
e
e
rin
g
fro
m
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TU
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k
in
a
d
a
,
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d
ia,
in
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a
n
d
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lo
m
a
in
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m
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u
d
lav
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ll
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ru
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g
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n
e
e
rin
g
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ll
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g
e
.
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re
se
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rc
h
in
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sts
in
c
lu
d
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wire
les
s
c
o
m
m
u
n
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n
s,
e
m
b
e
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e
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sy
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m
s
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n
d
v
ls
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d
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n
.
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h
a
s
p
u
b
li
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h
e
d
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se
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rc
h
p
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p
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v
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ri
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u
s
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n
tern
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ti
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n
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l
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u
r
n
a
ls
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n
d
c
o
n
fe
re
n
c
e
s.
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re
se
n
tl
y
h
e
is wo
rk
i
n
g
a
s As
so
c
iate
p
ro
fe
ss
o
r
in
th
e
d
e
p
a
rtme
n
t
o
f
ECE
,
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iv
e
rsa
l
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ll
e
g
e
o
f
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g
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n
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e
rin
g
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n
d
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h
n
o
l
o
g
y
,
G
u
n
tu
r,
AP,
5
2
2
4
3
8
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
k
o
ti
u
c
e
t@g
m
a
il
.
c
o
m
.
Mr
.
S
u
b
b
ia
h
Mu
r
u
g
a
n
is an
Ad
ju
n
c
t
P
ro
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ss
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r,
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a
v
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e
th
a
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c
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g
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g
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a
v
e
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th
a
In
stit
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te
o
f
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d
ica
l
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n
d
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h
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ica
l
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c
ien
c
e
s,
Ch
e
n
n
a
i,
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il
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d
u
,
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d
ia.
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p
u
b
li
sh
e
d
h
is
re
se
a
rc
h
a
rti
c
les
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m
a
n
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n
tern
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ti
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n
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l
a
n
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ti
o
n
a
l
c
o
n
fe
re
n
c
e
s
a
n
d
jo
u
rn
a
ls
.
His
re
se
a
rc
h
a
re
a
s
in
c
lu
d
e
n
e
two
rk
se
c
u
rit
y
a
n
d
m
a
c
h
i
n
e
lea
rn
i
n
g
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
sm
u
re
sju
r@g
m
a
il
.
c
o
m
.
Evaluation Warning : The document was created with Spire.PDF for Python.