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ca
p
a
b
le
o
f
r
em
e
m
b
er
in
g
p
r
e
v
io
u
s
in
p
u
t
v
alu
es
.
I
n
th
is
wo
r
k
,
s
ev
er
al
v
ar
ian
ts
o
f
R
NN
u
s
ed
f
o
r
an
d
r
o
id
m
alwa
r
e
d
etec
tio
n
.
T
h
e
p
r
o
p
o
s
ed
s
tu
d
y
ex
p
lo
r
es
t
h
e
ap
p
licatio
n
o
f
ad
v
a
n
ce
d
m
ac
h
in
e
lear
n
in
g
(
ML
)
a
n
d
d
ee
p
l
ea
r
n
in
g
(
DL
)
alg
o
r
ith
m
s
,
s
p
ec
if
ically
R
NN,
lo
n
g
s
h
o
r
t
-
ter
m
m
em
o
r
y
(
L
STM
)
,
Bi
-
L
STM
,
an
d
g
ated
r
ec
u
r
r
en
t
u
n
it
(
GR
U)
ar
ch
itectu
r
es,
to
d
ev
elo
p
a
co
m
p
r
eh
e
n
s
iv
e
m
alwa
r
e
d
etec
tio
n
m
o
d
el
th
at
ca
n
ef
f
ec
tiv
el
y
id
en
tify
an
d
class
if
y
An
d
r
o
id
m
alwa
r
e
b
ased
o
n
o
p
co
d
e
s
eq
u
en
ce
s
.
2.
RE
L
AT
E
D
WO
RK
S
Dick
ey
et
a
l
.
[
2
]
u
s
ed
ML
to
i
d
en
tify
An
d
r
o
id
m
alwa
r
e
i
n
s
tead
o
f
s
ig
n
atu
r
es.
T
h
e
au
th
o
r
s
p
r
o
ce
s
s
ed
m
alwa
r
e
b
in
ar
y
c
h
ar
ac
ter
is
tics
u
s
in
g
a
co
n
v
o
lu
tio
n
al
n
e
u
r
al
n
etwo
r
k
(
C
NN
)
an
d
tr
ee
-
b
ased
m
o
d
els.
T
h
ey
wer
e
8
7
%
-
9
0
%
ac
cu
r
ate.
T
h
e
r
esear
ch
ad
d
r
ess
ed
o
v
er
f
itti
n
g
,
n
o
tab
ly
in
tr
ee
-
b
ased
m
o
d
e
ls
,
an
d
s
h
o
wed
th
at
m
o
d
els
with
o
u
t
o
v
er
f
itti
n
g
p
er
f
o
r
m
e
d
co
n
s
is
ten
tly
th
r
o
u
g
h
o
u
t
tr
ain
i
n
g
a
n
d
test
in
g
.
Fatim
a
an
d
Kh
a
n
[
3
]
d
ev
elo
p
e
d
An
d
r
o
id
m
alwa
r
e
p
r
ed
ictio
n
alg
o
r
ith
m
s
u
tili
zin
g
v
ar
io
u
s
ap
p
p
er
m
is
s
io
n
s
d
atab
ase.
XGBo
o
s
t
with
g
r
ad
ien
t
b
o
o
s
tin
g
class
if
ier
en
s
em
b
le
lear
n
in
g
y
ield
e
d
8
1
.
4
7
%
ac
cu
r
ac
y
.
E
n
s
em
b
le
lear
n
in
g
ca
p
tu
r
e
d
co
m
p
licated
An
d
r
o
id
ap
p
b
e
h
av
io
r
s
b
etter
th
an
m
an
y
o
th
er
tech
n
iq
u
es,
in
clu
d
in
g
DL
.
I
n
ad
d
itio
n
to
DL
,
th
e
r
esear
ch
s
h
o
wed
h
o
w
ML
m
a
y
im
p
r
o
v
e
m
o
b
ile
s
ec
u
r
ity
.
V
an
u
s
h
a
et
a
l
.
[
4
]
em
p
lo
y
e
d
s
t
atic
An
d
r
o
i
d
APK
attr
ib
u
tes
to
d
is
tin
g
u
is
h
clea
n
f
r
o
m
m
alicio
u
s
a
p
p
s
.
T
h
e
s
tu
d
y
t
r
ain
ed
a
n
d
ev
alu
ated
f
iv
e
ML
m
o
d
els
u
s
in
g
th
e
Dr
eb
in
-
2
1
5
d
ataset:
d
ec
is
io
n
tr
ee
(
DT
)
,
s
u
p
p
o
r
t
v
ec
to
r
m
ac
h
in
e
(
SVM
)
with
r
ad
ial
b
asis
f
u
n
ctio
n
(
RBF
)
k
er
n
el
,
lo
g
is
tic
r
eg
r
ess
io
n
(
L
R
)
,
k
-
n
ea
r
est
n
eig
h
b
o
r
(
KNN)
,
an
d
Secu
Dr
o
id
n
eu
r
al
n
etwo
r
k
.
Static
f
ea
tu
r
e
-
b
ased
m
alwa
r
e
d
etec
tio
n
wo
r
k
ed
well
with
th
e
Secu
Dr
o
id
n
eu
r
al
n
etwo
r
k
.
G
u
an
d
Du
[
5
]
p
r
esen
ted
m
u
ltimo
d
al
n
eu
r
al
n
etwo
r
k
s
an
d
s
tatic
an
aly
s
is
f
o
r
An
d
r
o
id
m
alwa
r
e
d
etec
tio
n
.
T
h
i
s
m
eth
o
d
r
etr
iev
ed
p
er
m
is
s
io
n
s
,
o
p
co
d
es,
an
d
API
ca
ll
s
eq
u
en
ce
s
u
s
in
g
p
s
eu
d
o
-
d
y
n
am
ic
an
d
s
tatic
p
r
o
g
r
am
an
aly
ze
r
s
.
T
h
r
o
u
g
h
m
u
ltimo
d
al
n
eu
r
al
n
etwo
r
k
s
,
th
ese
v
ar
ied
f
ea
tu
r
es
wer
e
f
u
s
ed
an
d
class
if
ied
to
im
p
r
o
v
e
d
etec
tio
n
ac
cu
r
ac
y
.
T
h
e
Ma
lMe
m
d
ataset
s
h
o
wed
th
at
o
u
r
s
tr
ateg
y
o
u
tp
e
r
f
o
r
m
ed
p
r
ev
io
u
s
ap
p
r
o
ac
h
es in
d
etec
t
io
n
.
Ud
ay
ak
u
m
a
r
et
a
l
.
[
6
]
u
s
ed
g
lo
b
al
im
ag
e
s
h
ap
e
tr
a
n
s
f
o
r
m
(
GI
ST
)
ch
a
r
ac
ter
is
tics
f
r
o
m
g
r
ay
s
ca
le
ap
p
licatio
n
p
ictu
r
es
to
id
en
tif
y
An
d
r
o
id
m
alwa
r
e.
T
h
e
v
ir
u
s
s
h
ar
in
g
web
s
ite
in
clu
d
ed
m
alwa
r
e
an
d
b
e
n
ig
n
p
r
o
g
r
a
m
s
am
p
les.
T
o
r
ep
r
es
en
t
th
e
ap
p
licatio
n
s
’
g
lo
b
al
s
p
atial
ar
ch
itectu
r
e,
GI
ST
ch
ar
ac
ter
is
tics
wer
e
r
etr
iev
ed
f
r
o
m
g
r
ay
s
ca
le
p
h
o
to
s
.
T
h
e
a
p
p
s
wer
e
class
if
ied
u
s
in
g
LR
,
KNN,
an
d
Ad
aBo
o
s
t.
Ma
lwar
e
id
en
tific
atio
n
was
also
im
p
r
o
v
ed
u
s
in
g
a
f
ee
d
-
f
o
r
war
d
n
e
u
r
al
n
etwo
r
k
(
FF
NN)
o
v
er
s
tan
d
ar
d
class
if
ier
s
.
Od
at
an
d
Yaseen
[
7
]
p
r
o
p
o
s
ed
p
er
m
is
s
io
n
s
an
d
API
ca
lls
f
o
r
An
d
r
o
i
d
m
alwa
r
e
d
etec
tio
n
u
s
in
g
ML
.
T
h
e
m
o
d
el
r
e
v
ea
led
th
at
m
alwa
r
e
s
ee
k
s
u
n
u
s
u
al
co
m
b
in
atio
n
s
o
f
th
ese
tr
aits
co
m
p
ar
ed
to
h
ar
m
less
p
r
o
g
r
am
s
.
Fro
m
a
n
ew
d
ataset
o
f
p
e
r
m
is
s
io
n
s
an
d
API
r
eq
u
ests
at
d
if
f
er
en
t
lev
els,
th
e
FP
-
g
r
o
wth
al
g
o
r
ith
m
s
elec
ted
th
e
m
o
s
t
ess
en
tial
co
-
ex
is
tin
g
p
r
o
p
er
ties
.
Fo
r
An
d
r
o
id
m
alwa
r
e
ca
teg
o
r
izatio
n
,
r
an
d
o
m
f
o
r
e
st
(
R
F)
o
u
tp
er
f
o
r
m
ed
o
th
er
tr
a
d
itio
n
al
ML
alg
o
r
ith
m
s
.
On
th
e
Ma
lg
en
o
m
e
an
d
Dr
eb
in
d
atasets
,
s
tate
-
of
-
th
e
-
a
r
t
m
eth
o
d
s
wer
e
less
ac
cu
r
ate.
Awa
is
et
a
l
.
[
8
]
d
e
v
elo
p
ed
th
e
ANT
I
-
ANT
f
r
am
ewo
r
k
to
id
en
tif
y
an
d
p
r
ev
e
n
t
An
d
r
o
id
m
alwa
r
e
.
I
t
ex
tr
ac
ted
f
ea
tu
r
es
u
s
in
g
s
tat
ic
an
d
d
y
n
a
m
ic
an
aly
s
is
an
d
th
r
ee
-
lay
er
d
etec
tio
n
.
SVM
an
d
lo
g
is
tic
r
eg
r
ess
o
r
wer
e
u
s
ed
f
o
r
class
if
icatio
n
.
T
h
e
ar
ch
itectu
r
e
was
ac
cu
r
ate
o
n
th
e
C
C
C
S
-
C
I
C
-
An
d
Ma
l
-
2
0
2
0
d
ataset,
with
SVM
p
er
f
o
r
m
in
g
b
est.
Ma
h
in
d
r
u
et
a
l
.
[
9
]
in
tr
o
d
u
ce
d
“
Yar
o
wsk
y
Dr
o
id
,
”
a
s
em
i
-
s
u
p
er
v
is
ed
ML
an
d
f
ed
er
ated
lear
n
in
g
m
eth
o
d
to
id
en
tify
m
alwa
r
e
-
in
f
ec
te
d
ap
p
licatio
n
s
wh
ile
p
r
o
tectin
g
u
s
er
p
r
iv
ac
y
.
L
o
ca
lly
in
s
talled
ap
p
s
o
n
ce
llp
h
o
n
es
c
o
llected
d
ata
to
en
h
an
ce
th
e
d
etec
tin
g
alg
o
r
ith
m
.
On
5
0
,
0
0
0
m
alwa
r
e
-
f
r
ee
an
d
2
5
,
0
0
0
m
alicio
u
s
p
r
o
g
r
am
d
o
wn
lo
ad
s
,
th
e
f
r
am
ewo
r
k
s
h
o
wed
g
o
o
d
d
etec
tio
n
r
ates
with
f
ed
er
ated
lear
n
in
g
ac
r
o
s
s
d
if
f
er
en
t
u
s
er
s
.
Su
b
ash
et
a
l
.
[
1
0
]
u
s
ed
s
tatic
p
er
m
is
s
io
n
s
an
d
ML
to
id
en
tif
y
An
d
r
o
id
m
alwa
r
e.
T
h
e
An
d
r
o
id
API
u
s
e
s
t
u
d
y
f
o
u
n
d
s
u
s
p
ec
ted
m
alicio
u
s
ac
ti
v
ities
in
3
9
8
An
d
r
o
id
ap
p
s
.
A
f
ter
p
r
e
p
r
o
ce
s
s
in
g
,
n
aiv
e
b
ay
es,
d
ec
is
io
n
tr
e
e,
an
d
k
-
n
eig
h
b
o
r
s
wer
e
c
o
m
p
a
r
ed
.
B
ag
h
ir
o
v
[
1
1
]
test
ed
ML
tec
h
n
iq
u
es
f
o
r
An
d
r
o
id
m
alwa
r
e
d
etec
tio
n
u
s
in
g
b
en
ig
n
an
d
d
an
g
er
o
u
s
ap
p
licatio
n
s
.
T
h
e
alg
o
r
ith
m
s
’
ac
cu
r
ac
y
,
p
r
ec
is
io
n
,
r
ec
all,
an
d
F1
-
s
co
r
e
wer
e
ev
alu
ated
.
L
i
g
h
tGB
M
p
er
f
o
r
m
ed
b
est
ac
r
o
s
s
all
cr
iter
ia,
in
d
ica
tin
g
it
m
ig
h
t
b
e
u
s
ed
f
o
r
An
d
r
o
id
m
alwa
r
e
d
etec
tio
n
.
C
h
o
wd
h
u
r
y
et
a
l
.
[
1
2
]
p
r
o
v
id
e
d
a
co
m
p
r
eh
e
n
s
iv
e
r
e
v
iew
o
f
An
d
r
o
id
m
alwa
r
e
d
e
tectio
n
tec
h
n
iq
u
es
u
s
in
g
ML
.
I
t
co
v
er
ed
v
ar
io
u
s
s
u
p
er
v
is
ed
,
u
n
s
u
p
er
v
is
ed
,
a
n
d
DL
ap
p
r
o
ac
h
es,
co
m
p
ar
ed
th
eir
p
er
f
o
r
m
an
ce
,
an
d
d
is
cu
s
s
ed
th
e
m
etr
ics
u
s
ed
f
o
r
ev
al
u
atin
g
th
eir
ef
f
ec
tiv
e
n
ess
.
L
ak
s
h
m
an
ar
ao
et
a
l.
[
1
3
]
test
ed
ML
tech
n
iq
u
es
f
o
r
AM
D
u
s
in
g
a
d
ataset
o
f
b
en
ig
n
an
d
d
an
g
e
r
o
u
s
ap
p
lica
tio
n
s
.
T
h
e
s
tick
in
g
was
ev
alu
ated
o
n
ac
cu
r
ac
y
,
p
r
ec
is
io
n
,
r
ec
all,
an
d
F1
-
s
co
r
e.
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
8
,
No
.
2
,
May
20
2
5
:
1
1
0
6
-
1
1
1
4
1108
T
wo
ty
p
es
o
f
s
tack
in
g
n
am
ely
b
len
d
in
g
an
d
s
tack
in
g
ap
p
lie
d
an
d
r
ep
o
r
ted
g
o
o
d
r
esu
lts
.
D
o
ğ
an
ay
an
d
B
ü
lb
ü
l
[
1
4
]
em
p
lo
y
ed
ML
to
id
e
n
tif
y
An
d
r
o
id
m
alwa
r
e
u
s
in
g
th
e
Dr
eb
in
d
ataset
’
s
ex
ten
s
iv
e
s
tatic
an
d
d
y
n
am
ic
p
r
o
p
er
ties
.
T
h
e
d
ataset
was
r
ed
u
ce
d
to
m
a
n
if
est
f
i
le
p
er
m
is
s
io
n
s
f
o
r
s
p
ee
d
ier
d
etec
tio
n
.
ML
alg
o
r
ith
m
s
in
clu
d
ed
RF
,
n
aiv
e
b
ay
es
,
J
4
8
,
an
d
Ad
aBo
o
s
t.
An
d
r
o
id
m
alwa
r
e
d
etec
tio
n
was
b
etter
u
s
in
g
th
e
RF
m
eth
o
d
.
Sh
ar
m
a
an
d
San
g
al
[
1
5
]
u
s
ed
ML
to
id
en
tify
An
d
r
o
id
m
alw
ar
e
o
n
th
e
C
I
C
I
n
v
esAn
d
Ma
l2
0
1
9
d
ataset,
wh
ich
f
o
cu
s
es
o
n
p
er
m
is
s
io
n
s
an
d
i
n
ten
ts
.
PC
A
s
elec
ted
f
ea
tu
r
es
.
T
h
e
d
ataset
was
an
aly
ze
d
u
s
in
g
Naiv
e
B
ay
es
(
NB
)
,
d
ec
is
io
n
tr
ee
class
if
ier
(
DT
C
)
,
R
F,
an
d
K
NN.
RF
wa
s
th
e
m
o
s
t su
cc
ess
f
u
l b
in
ar
y
a
n
d
m
alwa
r
e
ca
teg
o
r
y
class
if
ier
.
Sm
m
ar
war
et
a
l
.
[
1
6
]
s
u
g
g
ested
XAI
-
A
MD
-
DL
,
an
e
x
p
lain
a
b
le
AI
-
b
ased
h
y
b
r
id
m
o
d
el
f
o
r
An
d
r
o
id
m
alwa
r
e
d
etec
tio
n
,
u
s
in
g
C
NNs
an
d
B
i
-
GR
Us.
R
esear
ch
tack
led
th
e
im
p
o
r
tan
t
p
r
o
b
lem
o
f
in
cr
ea
s
in
g
DL
m
o
d
el
i
n
ter
p
r
etab
ilit
y
wh
ile
r
etain
in
g
h
ig
h
d
etec
tio
n
ac
cu
r
ac
y
.
T
h
e
XAI
-
AM
D
-
DL
m
o
d
el
o
u
tp
er
f
o
r
m
ed
co
n
v
en
tio
n
al
D
L
ap
p
r
o
ac
h
es
.
L
ak
s
h
m
a
n
ar
ao
an
d
Sh
ash
i
[1
7
]
a
d
d
r
ess
ed
t
h
e
s
h
o
r
tco
m
i
n
g
s
o
f
s
ig
n
atu
r
e
-
b
ased
m
alwa
r
e
d
et
ec
tio
n
,
n
o
tab
ly
a
g
ain
s
t
ad
v
a
n
ce
d
An
d
r
o
id
m
alwa
r
e
o
b
f
u
s
c
atio
n
.
T
h
e
au
th
o
r
s
p
r
esen
ted
a
f
r
am
ewo
r
k
to
ex
t
r
ac
t
An
d
r
o
id
ap
p
p
er
m
is
s
io
n
s
,
o
p
co
d
es,
API
p
ac
k
a
g
es,
s
y
s
tem
ca
lls
,
in
ten
ts
,
an
d
API
ca
lls
.
RF
w
a
s
in
itially
th
e
m
o
s
t
ac
cu
r
ate
class
if
ier
.
T
h
e
wo
r
k
u
s
ed
m
u
ltil
ay
er
a
u
to
e
n
co
d
er
s
f
o
r
f
ea
tu
r
e
ex
tr
ac
tio
n
an
d
a
RF
class
if
ier
to
im
p
r
o
v
e
d
etec
tio
n
ac
cu
r
a
cy
.
R
ea
l
-
wo
r
ld
d
atasets
s
h
o
wed
th
at
th
is
in
teg
r
ated
tech
n
iq
u
e
ca
n
d
etec
t
An
d
r
o
i
d
m
alwa
r
e
with
e
x
ce
llen
t
a
cc
u
r
a
cy
.
Salah
et
a
l
.
[
1
8
]
ad
d
r
ess
ed
th
e
i
n
cr
ea
s
ed
n
ee
d
f
o
r
au
to
m
ated
m
alwa
r
e
d
etec
t
io
n
in
An
d
r
o
id
ap
p
licatio
n
s
d
u
e
to
m
o
b
ile
p
h
o
n
e
u
s
e
an
d
p
r
iv
ac
y
an
d
s
ec
u
r
ity
co
n
ce
r
n
s
.
An
aly
s
is
o
f
p
r
o
g
r
a
m
p
er
m
is
s
io
n
s
id
en
tifie
d
s
tati
c
m
alwa
r
e.
A
lar
g
e
ap
p
licatio
n
d
atase
t
was
u
s
ed
to
ca
lcu
late
p
er
m
is
s
io
n
s
.
T
h
e
s
tu
d
y
class
if
ied
th
ese
f
ea
tu
r
es u
s
in
g
tr
ee
-
b
ased
ML
.
Gu
y
to
n
et
a
l
.
[
1
9
]
co
n
s
id
er
ed
An
d
r
o
id
m
alwa
r
e
d
etec
tio
n
f
ea
tu
r
e
s
elec
tio
n
,
a
k
ey
b
u
t
o
f
te
n
o
v
er
lo
o
k
ed
f
ac
to
r
.
I
t
ev
alu
ate
d
1
1
f
ea
tu
r
e
s
elec
tio
n
ap
p
r
o
a
ch
es
o
n
th
r
ee
An
d
r
o
id
f
ea
tu
r
e
s
ets
-
p
er
m
is
s
io
n
s
,
i
n
ten
ts
,
an
d
API
c
alls
u
s
in
g
ML
clas
s
if
ier
s
.
Gu
p
ta
an
d
An
n
e
[
2
0
]
co
m
p
ar
ed
ML
m
alwa
r
e
d
etec
tio
n
tech
n
o
lo
g
ies
to
co
n
v
en
tio
n
al
m
eth
o
d
s
.
I
t
ass
ess
ed
th
r
ee
ML
m
o
d
els
f
o
r
h
a
r
m
f
u
l
s
o
f
t
war
e
d
etec
tio
n
a
n
d
d
escr
i
b
ed
th
eir
ac
cu
r
ac
y
an
d
ef
f
icien
cy
.
L
ee
et
a
l
.
[
2
1
]
ex
am
in
ed
An
d
r
o
id
m
alwa
r
e
d
etec
tio
n
f
ea
tu
r
e
s
elec
tio
n
u
s
in
g
g
en
etic
alg
o
r
i
th
m
s
.
Gen
etic
alg
o
r
ith
m
-
b
ase
d
f
ea
tu
r
e
s
elec
tio
n
en
h
an
ce
d
m
alwa
r
e
d
etec
tio
n
p
er
f
o
r
m
an
ce
an
d
tim
e
e
f
f
ici
en
cy
.
Ma
n
to
r
o
et
a
l
.
[
2
2
]
u
s
ed
d
y
n
am
ic
an
aly
s
is
in
th
e
m
o
b
ile
s
ec
u
r
ity
f
r
am
ewo
r
k
to
id
e
n
tify
An
d
r
o
id
m
alwa
r
e,
esp
ec
ially
o
b
f
u
s
ca
to
r
s
.
A
p
er
ce
n
ta
g
e
o
f
m
al
war
e
s
am
p
les
wer
e
id
en
tifie
d
u
s
in
g
d
y
n
am
ic
an
aly
s
is
.
T
h
o
u
g
h
s
u
cc
ess
f
u
l,
th
e
s
o
lu
tio
n
s
u
f
f
er
ed
h
ar
d
wa
r
e
r
estrictio
n
s
an
d
em
u
lato
r
ap
p
l
icatio
n
b
e
h
av
io
r
u
n
p
r
e
d
ictab
ilit
y
.
T
o
o
v
er
c
o
m
e
d
ataset
q
u
ality
,
W
an
g
et
a
l
.
[
2
3
]
p
r
esen
ted
s
elec
tiv
e
en
s
em
b
le
lear
n
in
g
f
o
r
An
d
r
o
id
m
alwa
r
e
d
etec
ti
o
n
.
T
h
e
ev
o
l
u
tio
n
ar
y
alg
o
r
it
h
m
s
elec
ts
th
e
to
p
co
m
p
o
n
en
t
lear
n
er
s
,
m
a
k
in
g
t
h
e
m
o
d
el
m
o
r
e
r
esil
ien
t
to
w
ea
k
tr
ain
in
g
d
ata.
T
h
e
f
in
d
in
g
s
s
h
o
wed
th
at
th
e
s
u
g
g
ested
An
d
r
o
id
m
alwa
r
e
d
etec
tio
n
ap
p
r
o
ac
h
was
m
o
r
e
r
esil
ien
t
an
d
ef
f
ec
tiv
e
.
Han
et
a
l
.
[
2
4
]
u
s
ed
API
ca
lls
as
ch
ar
ac
ter
is
tics
to
id
e
n
tify
f
r
a
u
d
u
len
t
An
d
r
o
id
ap
p
s
in
a
lar
g
e,
s
p
ar
s
e
d
ataset.
A
lar
g
e
d
ataset
o
f
An
d
r
o
id
ap
p
s
an
d
f
ea
tu
r
es
wa
s
em
p
lo
y
ed
.
Usi
n
g
SVM,
a
m
ac
h
in
e
-
lear
n
in
g
s
tr
ateg
y
f
o
r
m
alicio
u
s
ap
p
licatio
n
d
etec
tio
n
p
e
r
f
o
r
m
ed
c
o
m
p
etiti
v
ely
.
J
h
asi
et
a
l
.
[
2
5
]
e
x
am
in
ed
An
d
r
o
id
m
alwa
r
e,
s
p
ec
if
ic
ally
f
r
o
m
ap
p
s
th
at
ask
u
s
er
s
f
o
r
r
ig
h
ts
th
ey
m
ay
u
n
in
ten
tio
n
all
y
au
t
h
o
r
ize.
T
h
e
r
esear
ch
u
s
ed
ML
to
f
in
d
t
h
e
m
o
s
t
im
p
o
r
tan
t
p
er
m
is
s
io
n
s
f
o
r
ca
teg
o
r
izin
g
m
alwa
r
e
an
d
b
e
n
ig
n
a
p
p
s
.
3.
M
E
T
H
O
D
T
h
e
p
r
o
p
o
s
ed
m
eth
o
d
o
lo
g
y
is
s
h
o
wn
in
Fig
u
r
e
1
.
T
h
e
p
r
o
p
o
s
ed
m
o
d
el
f
o
r
an
d
r
o
id
m
alwa
r
e
d
etec
tio
n
u
s
in
g
L
STM
f
r
o
m
o
p
co
d
e
s
eq
u
e
n
ce
s
was
s
h
o
wn
in
F
ig
u
r
e
1
.
An
d
r
o
id
ap
k
s
ar
e
co
llected
(
b
o
th
m
alwa
r
e
an
d
n
o
n
-
m
alwa
r
e)
a
n
d
o
p
c
o
d
e
s
eq
u
en
ce
s
ar
e
e
x
tr
ac
ted
f
r
o
m
an
d
r
o
i
d
ap
p
s
.
Sm
a
li
f
iles
wer
e
cr
ea
ted
f
r
o
m
class
es.d
ex
f
iles
.
Deta
ils
ab
o
u
t
o
p
co
d
es
is
o
b
tain
ed
f
r
o
m
s
m
ali
f
iles
.
T
o
ex
tr
ac
t
th
e
f
ea
tu
r
es
,
a
p
y
th
o
n
u
tili
ty
ca
lled
“
An
d
r
o
g
u
ar
d
”
w
as
u
tili
ze
d
.
An
d
r
o
g
u
ar
d
co
m
e
s
with
a
n
u
m
b
er
o
f
i
n
s
tr
u
ctio
n
s
f
o
r
wo
r
k
in
g
with
An
d
r
o
id
ap
p
s
.
T
h
is
to
o
l
ca
n
b
e
in
s
talled
u
s
in
g
p
ip
.
I
t
is
a
ls
o
av
ailab
le
in
Ub
u
n
t
u
/Deb
ian
.
I
t
ca
n
b
e
ea
s
ily
in
s
talled
u
s
in
g
ap
t
co
m
m
a
n
d
i
n
u
b
u
n
tu
.
I
t
ca
n
also
b
e
d
ir
ec
t
ly
in
s
talled
th
r
o
u
g
h
g
it.
T
h
e
r
e
s
ev
er
al
co
m
m
an
d
s
av
ailab
le
in
an
d
r
o
g
u
ar
d
f
o
r
d
o
in
g
s
ev
er
al
o
p
er
atio
n
s
with
an
d
r
o
i
d
ap
p
licatio
n
s
.
“
an
d
r
o
g
u
ar
d
d
ec
o
m
p
ile
”
g
en
er
ates
co
n
tr
o
l
f
l
o
w
g
r
ap
h
s
(
C
FG)
f
o
r
th
e
s
p
ec
if
ied
an
d
r
o
id
ap
p
.
I
t
also
cr
ea
tes.ag
f
ile
s
(
s
m
ali
-
lik
e
f
o
r
m
)
f
o
r
all
o
f
th
e
d
ec
o
m
p
iled
class
es
an
d
m
eth
o
d
s
.
Op
co
d
e
s
eq
u
en
ce
s
ar
e
ex
tr
ac
ted
u
s
in
g
th
e.
ag
f
iles
.
Af
ter
g
ettin
g
a
s
eq
u
en
ce
o
f
o
p
co
d
es,
v
ar
io
u
s
v
a
r
ian
ts
o
f
R
NN
n
am
ely
L
STM
,
B
i
-
L
STM
,
GR
U
ar
e
ap
p
lied
to
th
ese
s
eq
u
en
ce
s
f
o
r
d
etec
tio
n
o
f
an
d
r
o
id
m
alwa
r
e.
3
.
1
.
Da
t
a
c
o
llect
io
n
Ma
lwar
e
ap
p
licatio
n
s
ar
e
g
ath
er
ed
f
r
o
m
th
e
web
s
ite
“
v
ir
u
s
s
h
ar
e.
co
m
”
.
Ap
k
s
th
at
d
o
n
o
t
in
clu
d
e
m
alicio
u
s
s
o
f
twar
e
h
a
v
e
b
ee
n
s
elec
ted
f
r
o
m
a
p
k
p
u
r
e.
co
m
an
d
Play
Sto
r
e
.
I
n
th
e
c
o
llected
ap
k
s
,
1
0
0
0
m
alwa
r
e
ap
p
s
an
d
1
0
0
0
b
e
n
ig
n
ap
p
s
ar
e
u
s
ed
in
th
is
ex
p
er
i
m
en
t
.
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
A
n
d
r
o
id
ma
lw
a
r
e
d
etec
tio
n
th
r
o
u
g
h
o
p
co
d
e
s
eq
u
en
ce
s
u
s
in
g
d
ee
p
lea
r
n
in
g
…
(
A
n
n
emn
ee
d
i La
ksh
ma
n
a
r
a
o
)
1109
Fig
u
r
e
1
.
Pro
p
o
s
ed
m
et
h
o
d
o
lo
g
y
f
o
r
an
d
r
o
id
m
alwa
r
e
d
etec
t
io
n
3
.
2
.
Cre
a
t
io
n o
f
c
o
ntr
o
l f
lo
w
g
ra
ph
A
C
FG,
is
a
d
iag
r
am
th
at
s
h
o
ws
h
o
w
co
n
tr
o
l
m
o
v
e
th
r
o
u
g
h
an
ap
p
licatio
n
as
it
r
u
n
s
.
T
h
e
d
ata
f
lo
w
r
o
u
tes
in
a
C
FG
ar
e
r
ep
r
esen
ted
b
y
e
d
g
es,
wh
ile
th
e
b
a
s
ic
b
lo
ck
s
ar
e
r
ep
r
esen
ted
b
y
n
o
d
es.
T
h
e
C
FG
illu
s
tr
ates
al
l
o
f
th
e
p
o
s
s
ib
le
d
ir
ec
tio
n
s
th
at
m
ig
h
t
b
e
tak
en
wh
ile
a
p
r
o
g
r
am
m
ed
is
b
ein
g
r
u
n
.
So
,
it
is
im
p
o
r
tan
t
t
o
an
al
y
ze
C
FGs
f
o
r
d
if
f
e
r
en
tiatin
g
m
alwa
r
e
an
d
b
en
ig
n
ap
k
s
.
T
h
er
e
is
a
co
m
m
an
d
in
an
d
r
o
g
u
ar
d
f
o
r
cr
ea
tin
g
C
FGs
f
o
r
an
d
r
o
id
ap
k
s
.
3
.
3
.
O
pco
de
s
equence
ex
t
ra
c
t
io
n f
ro
m a
nd
ro
id a
pp
s
An
d
r
o
id
a
p
p
g
en
er
ates
m
u
ltip
l
e
f
iles
,
in
clu
d
in
g
th
e
class
es.d
ex
f
ile,
th
e
m
an
if
ests
f
ile,
th
e
ass
ets
f
ile,
an
d
th
e
r
ef
er
en
ce
f
iles
.
T
h
e
“
class
es.d
ex
”
co
n
tain
s
t
h
e
J
av
a
co
d
e
f
o
r
th
e
An
d
r
o
i
d
a
p
p
.
Sm
ali
f
iles
ar
e
r
etr
iev
ed
a
f
ter
d
ec
o
m
p
ilin
g
d
e
x
f
iles
.
T
h
e
n
u
m
b
e
r
o
f
o
p
co
d
e
s
eq
u
en
ce
s
v
ar
ies
f
r
o
m
o
n
e
ap
p
to
an
o
th
er
ap
p
.
T
h
e
d
ec
o
m
p
ile
co
m
m
an
d
cr
ea
tes
f
iles
with
an
ag
ex
ten
s
io
n
alo
n
g
with
C
FGs
.
On
e
ap
p
ca
n
p
r
o
d
u
ce
m
u
ltip
le
ag
f
iles
an
d
ea
c
h
o
f
th
ese
f
ile
s
is
ass
o
ciate
d
with
a
s
p
ec
if
ic
m
eth
o
d
.
Op
co
d
es
s
eq
u
en
ce
s
ar
e
ex
tr
ac
ted
f
r
o
m
th
ese
ag
f
iles
.
Fig
u
r
e
2
s
h
o
ws
s
am
p
le
C
FG
an
d
F
ig
u
r
e
3
s
h
o
ws
s
am
p
le
ag
f
ile
f
o
r
th
e
s
am
e
f
ile
.
T
h
e
o
p
co
d
es
u
s
ed
in
th
is
C
FG a
r
e
“
co
n
s
t/4
”
,
“
in
v
o
k
e
-
v
ir
tu
al
”
.
“
I
n
v
o
k
e
-
r
esu
lt
”
,
“
if
-
n
ez
”
,
a
n
d
“
in
v
o
k
e
-
v
ir
tu
al
”
.
T
h
e
ex
tr
ac
tio
n
o
f
o
p
co
d
e
s
e
q
u
en
ce
s
f
r
o
m
ag
f
iles
ar
e
d
o
n
e
with
b
elo
w
p
r
o
ce
s
s
.
T
h
e
p
r
o
ce
s
s
o
f
g
en
er
atin
g
o
p
c
o
d
e
s
eq
u
en
ce
s
f
r
o
m
an
APK
b
e
g
in
s
with
t
h
e
APK
f
ile,
alo
n
g
s
id
e
a
Dalv
ik
o
p
c
o
d
e
lis
t
an
d
an
in
itially
em
p
ty
o
p
c
o
d
e
s
eq
u
e
n
ce
lis
t.
Usi
n
g
th
e
An
d
r
o
g
u
ar
d
to
o
l,
th
e
APK
is
d
ec
o
m
p
iled
t
o
p
r
o
d
u
ce
a
n
o
u
t
p
u
t
f
o
ld
er
co
n
tain
in
g
v
ar
io
u
s
f
iles
,
in
clu
d
in
g
C
FGs
an
d
.
ag
f
il
es.
E
ac
h
.
ag
f
ile
is
th
en
p
r
o
c
ess
ed
b
y
r
ea
d
in
g
its
co
n
ten
ts
lin
e
b
y
lin
e,
c
o
m
p
ar
i
n
g
ea
ch
lin
e
with
th
e
Dalv
ik
o
p
co
d
e
lis
t,
an
d
a
d
d
in
g
m
atch
in
g
o
p
c
o
d
es
to
th
e
o
p
co
d
e
s
eq
u
en
ce
lis
t.
Fin
ally
,
an
y
o
p
c
o
d
e
s
eq
u
en
ce
with
f
e
wer
th
an
1
5
en
tr
ies
is
f
ilter
e
d
o
u
t
to
e
n
s
u
r
e
o
n
ly
s
ig
n
if
ican
t
s
eq
u
en
ce
s
a
r
e
r
etai
n
ed
f
o
r
f
u
r
t
h
er
a
n
aly
s
is
.
Fro
m
th
is
m
eth
o
d
,
it
is
o
b
s
er
v
e
d
th
at
it
cr
ea
tes
s
ev
er
al
C
FG
s
alo
n
g
with
ag
f
iles
in
a
n
o
u
tp
u
t
f
o
ld
e
r
.
All
th
e
o
u
tp
u
t
f
o
ld
er
s
ar
e
p
ar
s
ed
t
o
e
x
tr
ac
t
o
p
c
o
d
e
s
eq
u
en
ce
s
f
r
o
m
a
g
f
iles
.
Af
ter
ap
p
ly
in
g
al
g
o
r
ith
m
,
a
lis
t o
f
lis
ts
wi
th
o
p
co
d
es is
cr
ea
ted
.
L
ater
,
all
th
ese
o
p
co
d
e
s
eq
u
en
ce
s
ar
e
tr
an
s
f
o
r
m
ed
to
csv
f
ile
u
s
in
g
p
y
th
o
n
s
cr
ip
t.
T
h
e
p
y
t
h
o
n
s
cr
i
p
t
p
r
o
d
u
ce
s
n
csv
f
iles
(
h
er
e
n
is
n
u
m
b
er
o
f
a
p
k
s
)
f
o
r
all
ap
p
licatio
n
s
u
s
in
g
a
lo
o
p
s
tr
u
ctu
r
e.
E
ac
h
r
o
w
o
f
csv
f
ile
co
n
tain
s
o
p
co
d
e
s
eq
u
en
ce
s
f
o
r
o
n
e
ap
p
licatio
n
.
Af
ter
t
h
is
s
tep
,
all
th
e
o
p
c
o
d
e
s
eq
u
e
n
ce
s
ar
e
av
a
ilab
le
in
ex
ce
l f
ile
.
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
8
,
No
.
2
,
May
20
2
5
:
1
1
0
6
-
1
1
1
4
1110
Fig
u
r
e
2
.
Sam
p
le
C
FG
Fig
u
r
e
3
.
Sam
p
le
.
ag
f
ile
4.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
4
.
1
.
A
pp
ly
ing
RNN
I
n
th
e
f
ir
s
t
ex
p
er
im
en
t,
we
ap
p
lied
a
R
NN
to
th
e
o
p
co
d
e
s
e
q
u
en
ce
s
ex
tr
ac
ted
f
o
r
An
d
r
o
id
m
alwa
r
e
d
etec
tio
n
.
T
h
e
R
NN
m
o
d
el
was
d
esig
n
ed
with
th
r
ee
h
i
d
d
en
lay
er
s
co
n
s
is
tin
g
o
f
2
0
0
,
1
0
0
,
a
n
d
5
n
eu
r
o
n
s
,
r
esp
ec
tiv
ely
.
T
h
e
tr
ai
n
in
g
p
r
o
ce
s
s
in
v
o
lv
ed
a
b
atch
s
ize
o
f
6
4
,
a
lear
n
in
g
r
ate
o
f
0
.
0
0
1
,
an
d
was
c
o
n
d
u
cted
o
v
er
1
0
0
ep
o
ch
s
.
W
h
ile
th
e
R
NN
ef
f
ec
tiv
ely
ca
p
tu
r
e
d
te
m
p
o
r
al
d
ep
en
d
en
cies
in
th
e
o
p
co
d
e
s
eq
u
en
ce
s
,
it
s
tr
u
g
g
led
with
r
etain
in
g
lo
n
g
-
ter
m
d
e
p
en
d
e
n
cies,
lead
in
g
to
an
o
v
er
all
ac
cu
r
ac
y
o
f
8
7
%.
T
h
e
v
an
is
h
in
g
g
r
ad
ien
t
p
r
o
b
lem
in
h
e
r
en
t
in
R
NN
s
lik
ely
co
n
tr
ib
u
ted
to
th
is
m
o
d
er
ate
p
er
f
o
r
m
an
ce
,
p
ar
ticu
lar
ly
wh
en
h
an
d
lin
g
lo
n
g
e
r
s
eq
u
en
ce
s
.
4
.
2
.
Appl
y
ing
L
ST
M
T
o
im
p
r
o
v
e
o
n
th
e
lim
itatio
n
s
o
b
s
er
v
ed
with
th
e
R
NN,
a
L
S
T
M
n
etwo
r
k
was
im
p
lem
en
te
d
u
s
in
g
th
e
s
am
e
th
r
ee
h
id
d
en
la
y
er
s
(
2
0
0
,
1
0
0
,
an
d
5
n
eu
r
o
n
s
)
an
d
tr
ain
ed
o
v
er
1
0
0
ep
o
ch
s
.
L
STM
n
etwo
r
k
s
ar
e
d
esig
n
ed
to
b
etter
m
an
a
g
e
lo
n
g
-
ter
m
d
ep
e
n
d
en
cies
th
r
o
u
g
h
th
eir
in
ter
n
al
g
atin
g
m
ec
h
an
is
m
s
,
wh
ich
ad
d
r
ess
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
A
n
d
r
o
id
ma
lw
a
r
e
d
etec
tio
n
th
r
o
u
g
h
o
p
co
d
e
s
eq
u
en
ce
s
u
s
in
g
d
ee
p
lea
r
n
in
g
…
(
A
n
n
emn
ee
d
i La
ksh
ma
n
a
r
a
o
)
1111
th
e
v
an
is
h
in
g
g
r
ad
ie
n
t
is
s
u
e.
T
h
is
m
o
d
el
ac
h
iev
e
d
a
s
ig
n
if
i
ca
n
tly
h
ig
h
e
r
ac
cu
r
ac
y
o
f
9
6
%,
d
em
o
n
s
tr
atin
g
its
ef
f
ec
tiv
en
ess
in
d
if
f
er
en
tiatin
g
b
etwe
en
m
alicio
u
s
an
d
b
en
ig
n
o
p
c
o
d
e
s
eq
u
en
ce
s
.
T
h
e
L
STM
’
s
ab
ilit
y
to
p
r
eser
v
e
in
f
o
r
m
atio
n
o
v
er
lo
n
g
s
eq
u
en
ce
s
was
k
ey
to
its
s
u
p
er
io
r
p
e
r
f
o
r
m
an
ce
c
o
m
p
ar
ed
to
th
e
R
NN
.
Fig
u
r
e
4
s
h
o
ws
e
p
o
ch
wis
e
p
e
r
f
o
r
m
a
n
ce
o
f
L
STM
.
Fig
u
r
e
4
(
a
)
s
h
o
ws
e
p
o
ch
wis
e
ac
cu
r
ac
ies
an
d
F
ig
u
r
e
4
(
b
)
s
h
o
ws ep
o
ch
wis
e
lo
s
s
v
alu
es with
L
STM
.
L
ater
,
B
i
-
L
STM
also
ap
p
lied
an
d
ac
h
iev
ed
ac
c
u
r
ac
y
o
f
9
6
.
2
%
(
a)
(
b
)
Fig
u
r
e
4
.
E
p
o
ch
wis
e
(
a
)
ac
cu
r
ac
y
with
L
STM
an
d
(
b
)
lo
s
s
w
ith
L
STM
4
.
3
.
Appl
y
ing
G
RU
Fu
r
th
er
ex
p
er
im
en
tatio
n
was
co
n
d
u
cte
d
u
s
in
g
a
GR
U
n
etwo
r
k
,
w
h
ich
is
a
v
ar
ian
t
o
f
th
e
L
STM
th
at
s
im
p
lifie
s
th
e
g
atin
g
m
ec
h
a
n
is
m
s
wh
ile
m
ain
tain
in
g
th
e
ab
i
lity
to
h
an
d
le
lo
n
g
-
ter
m
d
e
p
e
n
d
en
cies.
T
h
e
GR
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m
o
d
el
was
co
n
f
ig
u
r
e
d
with
th
e
s
am
e
th
r
ee
h
id
d
en
lay
er
s
,
c
o
n
s
is
tin
g
o
f
2
0
0
,
1
0
0
,
a
n
d
5
n
eu
r
o
n
s
.
T
h
e
m
o
d
el
was
tr
ain
ed
u
n
d
er
th
e
s
am
e
co
n
d
itio
n
s
as
th
e
L
STM
.
T
h
e
GR
U
d
em
o
n
s
tr
ated
co
m
p
ar
a
b
le
p
e
r
f
o
r
m
an
ce
to
th
e
L
STM
,
with
a
s
lig
h
t
im
p
r
o
v
e
m
en
t
in
tr
ain
in
g
ef
f
icien
c
y
d
u
e
to
its
s
im
p
ler
ar
ch
itectu
r
e.
T
h
e
GR
U
ac
h
iev
ed
h
ig
h
ac
cu
r
ac
y
,
s
u
cc
ess
f
u
lly
ca
p
tu
r
in
g
th
e
tem
p
o
r
al
p
atter
n
s
in
th
e
o
p
co
d
e
s
eq
u
en
ce
s
an
d
ef
f
ec
tiv
ely
d
is
tin
g
u
is
h
in
g
b
etwe
en
m
alwa
r
e
an
d
b
en
i
g
n
ap
p
licatio
n
s
.
T
h
e
r
esu
lts
in
d
icate
th
at
GR
U
is
a
v
iab
le
alter
n
ativ
e
to
L
STM
,
o
f
f
er
i
n
g
a
g
o
o
d
b
ala
n
ce
b
etwe
en
ac
cu
r
ac
y
an
d
co
m
p
u
tatio
n
al
ef
f
icien
cy
.
4
.
4
.
Co
m
pa
riso
n o
f
RNN
v
a
ria
nts f
o
r
m
a
lwa
re
det
ec
t
io
n
T
h
e
s
tan
d
ar
d
R
NN
ac
h
iev
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a
n
ac
cu
r
ac
y
o
f
8
7
%
,
wh
ich
is
l
o
wer
co
m
p
ar
ed
to
t
h
e
L
STM
an
d
GR
U.
T
h
e
L
STM
m
o
d
el
p
er
f
o
r
m
ed
th
e
b
est,
r
ea
ch
in
g
an
ac
c
u
r
a
cy
o
f
9
6
%,
Bi
-
L
STM
g
iv
en
ac
cu
r
ac
y
o
f
9
5
.
6
%.
T
h
e
GR
U
m
o
d
el,
wh
ile
s
lig
h
tly
less
ac
cu
r
ate
th
an
L
STM
at
9
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o
f
f
e
r
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aster
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ain
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n
g
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d
g
o
o
d
o
v
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all
p
e
r
f
o
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m
a
n
ce
.
T
h
e
co
m
p
ar
is
o
n
h
ig
h
lig
h
ts
L
STM
as
th
e
m
o
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t
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f
ec
tiv
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with
GR
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as
a
s
tr
o
n
g
alter
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ativ
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wh
en
co
m
p
u
tatio
n
al
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f
icien
c
y
is
im
p
o
r
tan
t
.
Fig
u
r
e
5
s
h
o
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a
cc
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r
ac
y
c
o
m
p
ar
is
o
n
o
f
R
NN
v
ar
ian
ts
f
o
r
m
alwa
r
e
d
etec
tio
n
.
Fig
u
r
e
5
.
C
o
m
p
a
r
is
o
n
o
f
d
ee
p
lear
n
in
g
R
NN
v
ar
ian
ts
f
o
r
m
al
war
e
d
etec
tio
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
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-
4
7
52
In
d
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n
esian
J
E
lec
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n
g
&
C
o
m
p
Sci
,
Vo
l.
3
8
,
No
.
2
,
May
20
2
5
:
1
1
0
6
-
1
1
1
4
1112
5.
CO
NCLU
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esear
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ate
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v
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DL
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o
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s
p
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if
ically
R
NN,
L
STM
,
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d
GR
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T
h
e
s
tu
d
y
s
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o
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t
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ac
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e
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ig
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d
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n
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in
th
e
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ata.
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-
L
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r
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u
ce
d
a
g
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o
d
ac
cu
r
ac
y
o
f
9
5
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6
%
f
o
r
m
alwa
r
e
d
etec
tio
n
.
GR
U,
with
an
ac
cu
r
ac
y
o
f
9
3
%,
p
r
o
v
ed
to
b
e
a
s
tr
o
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g
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n
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f
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g
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g
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o
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a
n
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an
d
c
o
m
p
u
tatio
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al
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f
icien
cy
.
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h
e
s
tan
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ar
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in
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Ov
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th
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k
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tial
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tech
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iq
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in
en
h
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m
alwa
r
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tio
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ca
p
ab
ilit
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h
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th
at
f
u
r
th
e
r
e
x
p
lo
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o
f
th
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m
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p
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s
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ly
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co
r
p
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d
d
it
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f
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tu
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co
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ld
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d
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ate
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s
.
RE
F
E
R
E
NC
E
S
[
1
]
A
.
La
k
sh
ma
n
a
r
a
o
a
n
d
M
.
S
h
a
s
h
i
,
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A
n
d
r
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d
M
a
l
w
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e
t
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t
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w
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t
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D
e
e
p
Le
a
r
n
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n
g
u
si
n
g
R
N
N
f
r
o
m
O
p
c
o
d
e
S
e
q
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e
n
c
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s
,
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n
t
e
rn
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t
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a
l
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o
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r
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l
o
f
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n
t
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ra
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t
i
v
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Mo
b
i
l
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c
h
n
o
l
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e
s
(
i
J
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M),
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.
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,
n
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.
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p
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6
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2
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3
.
[
2
]
K
.
D
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c
k
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.
H
w
a
n
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,
a
n
d
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.
K
i
m,
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n
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l
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r
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o
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h
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p
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A
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d
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d
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o
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a
st
C
o
n
2
0
2
4
,
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t
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.
[
3
]
N
.
F
a
t
i
m
a
a
n
d
H
.
F
.
K
h
a
n
,
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c
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o
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st
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s
(
I
C
ET
S
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)
,
M
a
n
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ma,
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,
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p
.
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3
.
[
4
]
D
.
V
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n
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s
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a
,
S
.
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n
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h
,
A
.
B
.
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d
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.
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.
S
,
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u
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:
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a
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o
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st
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c
f
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t
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s
,
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2
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4
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t
e
rn
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t
i
o
n
a
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f
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o
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d
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m
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c
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t
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s
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.
[
5
]
F
.
G
u
a
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d
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.
D
u
,
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u
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,
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d
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rn
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S
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.
[
6
]
P
.
U
d
a
y
a
k
u
m
a
r
,
S
.
Y
a
l
a
ma
t
i
,
L.
M
o
h
a
n
,
M
.
J.
H
a
q
u
e
,
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.
N
a
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k
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d
e
,
a
n
d
K
.
M
.
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h
a
s
h
y
a
m,
“
A
n
d
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o
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d
m
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w
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d
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.
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2
.
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JN
T
Un
iv
e
rsit
y
,
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k
i
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d
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in
2
0
1
0
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n
d
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Tec
h
.
(C
S
E)
d
e
g
re
e
fro
m
JN
T
U
n
iv
e
rsit
y
,
H
y
d
e
ra
b
a
d
in
2
0
0
5
.
He
is
P
u
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n
g
P
h
.
D.
(C
S
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i
n
S
a
th
y
a
b
a
m
a
In
stit
u
te
o
f
S
c
ien
c
e
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Tec
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lo
g
y
(De
e
m
e
d
to
b
e
U
n
iv
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y
),
Ch
e
n
n
a
i.
He
h
a
s
m
o
re
t
h
a
n
1
7
y
e
a
rs
’
e
x
p
e
rien
c
e
in
t
e
a
c
h
in
g
a
n
d
ra
ti
fi
e
d
a
s
a
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t
p
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ss
o
r
b
y
JN
T
Un
iv
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rsit
y
,
Ka
k
i
n
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d
a
.
His
a
re
a
s
o
f
in
tere
st
in
c
lu
d
e
m
a
c
h
in
e
lea
rn
in
g
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p
r
in
c
ip
les
o
f
c
o
m
p
il
e
r
d
e
sig
n
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a
rti
ficia
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ra
l
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two
rk
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d
d
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p
lea
rn
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n
e
two
rk
se
c
u
rit
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a
n
d
th
e
o
r
y
o
f
c
o
m
p
u
tati
o
n
.
He
h
a
s
p
re
se
n
ted
a
ro
u
n
d
1
2
re
se
a
rc
h
p
a
p
e
rs
in
In
ter
n
a
ti
o
n
a
l
Co
n
fe
re
n
c
e
s,
p
u
b
li
sh
e
d
a
ro
u
n
d
1
0
re
se
a
rc
h
a
rti
c
les
fro
m
h
is
re
se
a
rc
h
fin
d
in
g
in
v
a
rio
u
s
re
p
u
ted
In
tern
a
ti
o
n
a
l
Jo
u
rn
a
ls
a
n
d
2
In
d
ian
p
a
ten
ts.
He
h
a
s
b
e
e
n
a
n
a
c
ti
v
e
m
e
m
b
e
r
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f
se
v
e
ra
l
p
ro
fe
ss
io
n
a
l
so
c
ieties
li
k
e
IS
TE
,
CS
I,
IAENG
.
He
h
a
s
re
c
e
iv
e
d
a
wa
rd
s
a
s
b
e
st
tea
c
h
e
r,
b
e
st
a
c
a
d
e
m
icia
n
a
n
d
b
e
st
re
se
a
rc
h
e
r
fo
r
h
is
a
c
a
d
e
m
ic
a
n
d
re
se
a
rc
h
wo
rk
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
tk
rish
n
a
k
ish
o
re
@k
l
u
n
i
v
e
rsity
.
in
.
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
8
,
No
.
2
,
May
20
2
5
:
1
1
0
6
-
1
1
1
4
1114
Dr
.
Pa
v
a
n
S
a
th
is
h
Cha
n
d
a
k
a
P
a
v
a
n
S
a
t
h
ish
C
h
a
n
d
a
k
a
wo
rk
i
n
g
in
t
h
e
De
p
a
rtme
n
t
o
f
CS
E
a
t
C
h
a
it
a
n
y
a
En
g
i
n
e
e
rin
g
Co
l
leg
e
,
Visa
k
h
a
p
a
tn
a
m
,
An
d
h
ra
P
ra
d
e
sh
,
In
d
ia.
He
is h
a
v
in
g
9
y
e
a
rs o
f
a
c
a
d
e
m
ic ex
p
e
rien
c
e
a
n
d
5
y
e
a
rs o
f
re
se
a
rc
h
e
x
p
e
rti
se
.
His wo
rk
p
rima
ril
y
fo
c
u
se
s
o
n
m
e
d
ica
l
ima
g
e
se
g
m
e
n
tatio
n
u
si
n
g
m
a
c
h
in
e
a
n
d
d
e
e
p
lea
rn
in
g
tec
h
n
iq
u
e
s.
He
h
a
s p
u
b
li
sh
e
d
se
v
e
ra
l
a
rti
c
les
in
re
p
u
ted
jo
u
rn
a
ls.
H
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
p
a
v
a
n
sa
ti
sh
c
h
@
g
m
a
il
.
c
o
m
.
Chi
n
ta
Ve
n
k
a
t
a
Mu
r
a
li
K
r
ish
n
a
c
u
rre
n
tl
y
w
o
rk
in
g
a
s
a
ss
o
c
i
a
te
p
ro
fe
ss
o
r
a
n
d
HO
D
in
CS
E
(Da
ta
S
c
ien
c
e
)
d
e
p
a
rtme
n
t
a
t
NRI
In
sti
tu
te
o
f
Tec
h
n
o
l
o
g
y
.
He
is
a
m
e
m
b
e
r
o
f
IAENG
,
IF
ERP
,
a
n
d
INSC.
He
c
o
m
p
lete
d
h
is
M
.
Tec
h
.
in
C
o
m
p
u
t
e
r
S
c
ien
c
e
a
n
d
En
g
in
e
e
rin
g
in
2
0
0
9
a
n
d
is
c
u
rre
n
tl
y
p
u
rs
u
in
g
a
P
h
.
D.
in
Co
m
p
u
ter
S
c
ien
c
e
a
n
d
En
g
in
e
e
rin
g
a
t
G
ITAM
(De
e
m
e
d
to
b
e
U
n
iv
e
rsit
y
),
Visa
k
h
a
p
a
tn
a
m
.
He
h
a
s
p
u
b
l
ish
e
d
re
se
a
rc
h
p
a
p
e
rs
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n
v
a
rio
u
s
c
o
n
fe
re
n
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e
s
a
n
d
j
o
u
r
n
a
ls
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n
d
h
a
s
b
e
e
n
g
ra
n
ted
t
h
re
e
p
a
ten
ts
wit
h
te
n
o
th
e
rs
in
t
h
e
p
ip
e
li
n
e
f
o
r
th
e
g
ra
n
t.
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o
u
r
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f
h
is
b
o
o
k
s
h
a
v
e
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e
n
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b
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d
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y
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tern
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l
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n
d
n
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ti
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n
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l
p
u
b
li
sh
in
g
a
g
e
n
c
ies
.
He
wa
s
a
wa
rd
e
d
th
e
“
Be
st
Re
se
a
rc
h
e
r
Aw
a
rd
”
fro
m
IOSRD
in
2
0
1
8
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
m
u
ra
li
k
rish
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_
c
h
in
ta2
0
0
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@
y
a
h
o
o
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c
o
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in
.
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d
h
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r
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a
d
h
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n
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m
a
r
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tt
y
is
wo
r
k
in
g
a
s
a
n
a
ss
istan
t
p
r
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fe
ss
o
r
,
De
p
t.
o
f
I
n
fo
rm
a
ti
o
n
Tec
h
n
o
l
o
g
y
in
R.
V.R
a
n
d
J.C
C
o
ll
e
g
e
o
f
E
n
g
in
e
e
rin
g
,
G
u
n
tu
r,
A
n
d
h
ra
P
ra
d
e
sh
,
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n
d
ia.
He
is p
u
rs
u
in
g
h
is
P
h
.
D.
fr
o
m
JN
TU
Ka
k
i
n
a
d
a
i
n
t
h
e
a
re
a
o
f
m
a
c
h
in
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lea
rn
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g
.
He
h
a
s
1
0
y
e
a
rs
o
f
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c
h
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e
x
p
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e
.
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h
a
d
p
u
b
li
s
h
e
d
p
a
p
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rs
in
re
p
u
te
d
Na
ti
o
n
a
l
a
n
d
In
tern
a
ti
o
n
a
l
J
o
u
r
n
a
ls.
He
h
a
d
a
t
ten
d
e
d
m
a
n
y
w
o
rk
sh
o
p
s
,
c
o
n
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re
n
c
e
s
a
n
d
p
re
se
n
ted
v
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rio
u
s
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se
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rc
h
p
a
p
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rs
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t
Na
ti
o
n
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l
a
n
d
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n
tern
a
ti
o
n
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l
c
o
n
fe
re
n
c
e
s.
His
a
re
a
s
o
f
i
n
tere
st
i
n
c
lu
d
e
ima
g
e
p
ro
c
e
ss
in
g
,
m
a
c
h
in
e
lea
rn
in
g
,
d
e
e
p
lea
rn
in
g
,
n
a
t
u
ra
l
lan
g
u
a
g
e
p
ro
c
e
ss
in
g
,
a
n
d
c
y
b
e
r
se
c
u
rit
y
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
m
a
d
h
a
n
jett
y
.
r
v
r@g
m
a
il
.
c
o
m
.
Evaluation Warning : The document was created with Spire.PDF for Python.