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h
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h
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MQ
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g
ate
w
a
y
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th
e
in
cr
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p
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(
P
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co
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in
g
to
th
e
MQ
T
T
p
r
o
to
co
l
s
p
ec
if
icatio
n
[
7
]
.
Sin
ce
t
h
e
MQ
T
T
p
r
o
to
co
l
im
p
le
m
e
n
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s
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"
p
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-
s
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cr
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"
p
atter
n
,
th
e
a
m
o
u
n
t
o
f
i
n
f
o
r
m
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cir
c
u
lati
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in
t
h
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n
et
w
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s
tr
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l
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ep
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d
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o
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th
e
n
u
m
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f
s
en
d
er
s
an
d
r
ec
ip
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,
as
w
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ll
as
o
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th
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Qo
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v
alu
e.
Ma
n
y
r
esear
ch
g
r
o
u
p
s
s
tu
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ied
th
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MQ
T
T
p
r
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to
co
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as
a
test
in
g
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ea
f
o
r
Do
S
attac
k
s
r
esear
ch
.
A
c
o
m
p
ar
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an
a
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is
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late
Do
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attac
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w
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i
n
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ab
le
1
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T
ab
le
1
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T
h
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m
p
ar
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o
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o
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r
e
lated
w
o
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k
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u
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ies
P
a
r
a
me
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e
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N
u
mb
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d
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v
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M
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Ev
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l
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me
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R
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f
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o
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1
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2
2
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0
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u
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l
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2
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scri
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t
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l
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y
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r
P
r
o
c
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ssi
n
g
t
i
me
[
8
]
T
C
P
p
a
c
k
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t
s
9
d
e
v
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c
e
s
NA
R
e
a
l
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a
l
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t
w
o
r
k
N
e
t
w
o
r
k
l
a
y
e
r
NA
[
9
]
-
5
d
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v
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c
e
s
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C
o
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t
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si
m
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l
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t
i
o
n
N
e
t
w
o
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k
l
a
y
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NA
[
1
0
]
Q
o
S
0
,
1
,
2
1
d
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v
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c
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-
R
e
a
l
p
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l
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P
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me
[
1
1
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NA
NA
NA
R
e
a
l
p
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t
w
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k
A
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t
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l
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y
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r
P
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t
i
me
[
1
2
]
Q
o
S
0
,
1
,
2
1
p
u
b
l
i
s
h
e
r
,
1
0
0
su
b
s
c
r
i
b
e
r
s
+
C
o
mp
u
t
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m
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l
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t
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A
p
p
l
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c
a
t
i
o
n
l
a
y
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r
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P
U
u
s
a
g
e
[
1
3
]
Q
o
S
0
,
1
,
2
1
0
0
p
u
b
l
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s
h
e
r
s
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C
o
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A
p
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l
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c
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t
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o
n
l
a
y
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r
P
r
o
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n
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t
i
me
[
1
4
]
Q
o
S
0
,
1
,
2
1
0
p
u
b
l
i
sh
e
r
s
-
C
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t
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si
m
u
l
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t
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p
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t
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o
n
l
a
y
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r
P
r
o
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ssi
n
g
t
i
me
[
1
5
]
4
M
B
p
a
y
l
o
a
d
2
0
0
0
p
u
b
l
i
s
h
e
r
s
NA
C
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t
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si
m
u
l
a
t
i
o
n
N
e
t
w
o
r
k
l
a
y
e
r
,
A
p
p
l
i
c
a
t
i
o
n
l
a
y
e
r
C
P
U
u
s
a
g
e
[
1
6
]
10
K
B
p
a
y
l
o
a
d
2
0
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0
p
u
b
l
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s
h
e
r
s
NA
C
o
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m
u
l
a
t
i
o
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N
e
t
w
o
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k
l
a
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e
r
,
A
p
p
l
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c
a
t
i
o
n
l
a
y
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r
P
r
o
c
e
ssi
n
g
t
i
me
;
C
P
U
u
s
a
g
e
[
1
7
]
Un
li
k
e
o
th
er
s
t
u
d
ies,
i
n
o
u
r
r
esear
ch
Do
S
attac
k
d
etec
tio
n
h
as
th
e
g
lo
b
al
ef
f
ec
t
o
f
a
lar
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er
n
u
m
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f
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ac
to
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co
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n
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to
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in
cr
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s
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w
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lo
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B
ased
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MQ
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p
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p
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Do
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.
2.
P
RO
P
O
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D
M
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h
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p
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s
s
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it
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a
P
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u
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Fig
u
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1
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T
h
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p
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s
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Evaluation Warning : The document was created with Spire.PDF for Python.
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J
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2502
-
4752
Do
S
a
tta
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s
d
etec
tio
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MQTT
n
etw
o
r
ks
(
Dmit
r
ii Dik
i
i
)
603
T
h
e
m
ai
n
f
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tu
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s
o
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P
T
m
ess
ag
e
in
cl
u
d
e
th
e
f
o
llo
w
i
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g
:
a)
th
e
titl
e
o
f
th
e
to
p
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m
e
s
s
a
g
e;
b)
th
e
v
al
u
e
o
f
t
h
e
Qo
S p
ar
a
m
ete
r
;
c)
th
e
p
a
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s
ize
;
d)
th
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v
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o
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lag
(
r
ep
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.
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f
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th
is
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y
p
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f
m
es
s
ag
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a)
th
e
n
et
w
o
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k
ad
d
r
ess
o
f
th
e
s
en
d
er
;
b)
th
e
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n
a
m
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f
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n
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;
c)
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D
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;
d)
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cr
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p
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ap
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tr
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s
;
e)
th
e
n
u
m
b
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o
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s
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s
cr
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s
.
T
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,
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m
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Do
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(
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u
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.
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d
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ize
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d
a
r
r
o
w
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in
F
ig
u
r
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2
)
.
W
h
en
t
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x
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PT
m
e
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ag
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a
r
r
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th
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r
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.
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m
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to
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in
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t
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d
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f
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s
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,
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t
i
s
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en
t
t
o
th
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g
a
t
ew
ay
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d
f
u
r
th
e
r
t
o
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u
b
s
c
r
i
b
e
r
s
.
T
o
d
e
s
i
g
n
a
n
a
tt
a
ck
d
et
e
c
ti
o
n
s
y
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em
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e
f
u
tu
r
e
v
e
c
t
o
r
t
h
a
t
w
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ll
b
e
ev
a
lu
a
te
d
b
y
th
e
an
a
ly
z
e
r
s
o
f
a
m
es
s
ag
e
,
s
h
o
u
l
d
b
e
d
e
f
in
e
d
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A
l
t
h
o
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g
h
in
c
r
e
as
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g
th
e
Q
o
S
v
al
u
e
is
in
s
ig
n
if
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c
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t
,
i
t
s
ti
l
l
af
f
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t
s
th
e
p
e
r
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e
o
f
th
e
g
at
ew
ay
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n
a
d
d
i
t
i
o
n
,
t
h
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i
s
a
n
o
b
v
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o
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s
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l
a
ti
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s
h
i
p
b
etw
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en
th
e
n
u
m
b
e
r
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f
s
u
b
s
c
r
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er
s
a
n
d
th
e
s
p
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o
f
p
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e
s
s
in
g
m
e
s
s
a
g
e
s
at
th
e
g
a
tew
ay
,
w
h
i
ch
w
as
n
o
t
r
ev
e
al
e
d
in
th
e
p
a
p
e
r
s
o
f
o
t
h
e
r
r
e
s
e
a
r
c
h
g
r
o
u
p
s
.
An
o
th
er
i
m
p
o
r
ta
n
t
p
ar
a
m
eter
o
f
th
is
m
es
s
ag
e
t
y
p
e
i
s
th
e
s
i
ze
o
f
th
e
p
ay
lo
ad
.
A
s
a
r
u
le,
th
e
d
ata
is
p
r
esen
ted
eith
er
in
p
lain
f
o
r
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o
r
in
J
SON
f
o
r
m
at.
XM
L
f
o
r
m
at
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u
s
ed
l
ess
f
r
eq
u
en
t
l
y
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T
h
e
MQ
T
T
p
r
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to
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l
s
u
p
p
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ts
s
e
n
d
in
g
m
e
s
s
a
g
es
u
p
to
2
5
6
m
eg
ab
y
tes
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n
s
ize.
T
o
d
eter
m
i
n
e
t
h
e
i
m
p
ac
t
o
f
t
h
e
p
ay
lo
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s
ize
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t
h
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v
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all
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er
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an
ce
o
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ate,
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ex
p
er
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s
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m
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av
e
b
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n
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er
f
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m
ed
in
t
h
e
s
t
u
d
y
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Me
s
s
ag
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s
w
it
h
a
f
e
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ay
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ad
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o
u
n
d
8
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w
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to
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w
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ess
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th
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Af
te
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Fi
g
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3
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t
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p
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T
h
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s
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tr
af
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is
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ap
ar
t
f
r
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m
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es
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it
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t
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id
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eir
s
ize,
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u
m
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o
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ip
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u
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3
.
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ate
w
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y
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t t
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af
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s
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u
s
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all
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s
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s
tati
s
tical
m
et
h
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d
s
an
d
m
ac
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g
m
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n
th
i
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,
w
e
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n
s
id
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s
u
c
h
a
l
g
o
r
ith
m
s
a
s
an
ar
ti
f
icial
n
eu
r
al
n
e
t
w
o
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k
(
m
u
ltil
a
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er
p
er
ce
p
tr
o
n
)
,
th
e
s
u
p
p
o
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t
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to
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m
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in
e,
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d
t
h
e
r
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d
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m
f
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e
s
t
al
g
o
r
ith
m
.
T
h
ese
t
h
r
ee
t
y
p
e
s
o
f
al
g
o
r
ith
m
s
ar
e
u
s
ed
to
cla
s
s
i
f
y
a
n
o
b
j
ec
t
b
y
a
f
i
n
ite
s
et
o
f
attr
ib
u
te
s
.
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h
e
m
ain
tas
k
o
f
o
u
r
r
esear
ch
is
t
o
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ev
ea
l
th
e
m
e
th
o
d
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at
s
h
o
w
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th
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est
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esu
lt
s
o
f
d
etec
tin
g
ab
n
o
r
m
al
b
eh
a
v
io
r
o
f
d
ev
ices b
ased
o
n
t
h
e
ch
ar
ac
t
er
is
tics
o
f
t
h
e
MQ
T
T
p
r
o
to
c
o
l
tr
af
f
ic.
2
.
1
.
Art
if
ici
a
l neura
l net
w
o
r
k
T
h
is
m
o
d
el
co
n
s
i
s
ts
o
f
a
n
et
wo
r
k
o
f
n
e
u
r
o
n
s
t
h
at
ar
e
d
iv
id
e
d
in
to
la
y
er
s
[
1
8
]
.
L
a
y
er
s
ar
e
d
iv
id
ed
in
to
in
p
u
t,
h
id
d
en
,
an
d
o
u
tp
u
t
la
y
e
r
s
.
T
h
e
n
u
m
b
er
o
f
in
p
u
t
f
ea
tu
r
es
o
f
an
o
b
j
ec
t
d
eter
m
in
e
s
th
e
n
u
m
b
er
o
f
n
eu
r
o
n
s
in
t
h
e
f
ir
s
t
la
y
er
.
T
h
e
o
u
tp
u
t
l
a
y
er
h
a
s
a
d
i
m
e
n
s
io
n
eq
u
al
to
th
e
n
u
m
b
er
o
f
cla
s
s
es.
Neu
r
o
n
s
o
f
n
ei
g
h
b
o
r
in
g
la
y
er
s
h
a
v
e
co
n
n
ec
tio
n
s
w
it
h
ea
ch
o
th
er
,
w
h
ic
h
ar
e
ca
lled
weig
h
t
co
ef
f
icie
n
ts
.
T
h
e
v
alu
e
o
f
a
n
eu
r
o
n
d
ep
en
d
s
o
n
all
in
co
m
in
g
w
ei
g
h
ts
a
n
d
v
alu
es o
f
t
h
e
p
r
ev
io
u
s
la
y
er
's n
eu
r
o
n
s
a
n
d
is
d
ef
i
n
ed
as:
∑
(
1
)
w
h
er
e
x
i
–
v
al
u
e
o
f
i
-
t
h
n
eu
r
o
n
o
f
th
e
p
r
e
v
io
u
s
la
y
er
,
w
i
i
s
th
e
v
alu
e
w
e
ig
h
t
co
n
n
ec
ti
n
g
i
-
t
h
n
e
u
r
o
n
o
f
t
h
e
p
r
ev
io
u
s
la
y
er
.
T
h
e
ac
tiv
atio
n
f
u
n
ctio
n
o
f
t
h
e
n
e
u
r
o
n
y
=
f
(
x
)
ca
n
b
e
r
ep
r
esen
ted
as
a
lin
ea
r
,
th
r
es
h
o
ld
,
o
r
s
ig
m
o
id
al
f
u
n
ct
io
n
.
T
h
is
s
t
u
d
y
u
s
ed
a
m
o
d
el
o
f
a
m
u
lt
il
a
y
er
p
er
ce
p
tr
o
n
w
it
h
t
h
e
f
u
n
ctio
n
o
f
ac
ti
v
ati
n
g
n
eu
r
o
n
s
i
n
th
e
f
o
r
m
o
f
a
s
ig
m
o
id
:
(
2
)
T
h
e
m
u
ltil
a
y
er
p
er
ce
p
tr
o
n
h
as
to
b
e
tr
ain
ed
to
f
in
d
th
e
m
o
s
t
ap
p
r
o
p
r
iate
v
alu
es
o
f
w
ei
g
h
t
co
ef
f
icie
n
t
s
.
T
r
ain
in
g
ca
n
b
e
ca
r
r
ied
o
u
t u
s
in
g
t
h
e
b
ac
k
p
r
o
p
ag
atio
n
al
g
o
r
ith
m
o
r
g
e
n
etic
a
l
g
o
r
ith
m
s
.
2
.
2
.
T
he
a
lg
o
rit
hm
o
f
ra
nd
o
m
f
o
re
s
t
T
h
e
r
an
d
o
m
f
o
r
est
al
g
o
r
ith
m
is
b
ased
o
n
t
h
e
ap
p
r
o
ac
h
i
m
p
le
m
e
n
ted
in
th
e
d
ec
i
s
io
n
tr
ee
alg
o
r
ith
m
.
T
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e
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o
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itio
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o
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th
e
r
a
n
d
o
m
f
o
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est
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n
s
i
s
ts
o
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m
a
n
y
tr
ee
s
[
1
9
]
.
E
ac
h
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ec
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e
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o
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est
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ased
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o
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y
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d
[
2
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m
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ai
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ased
o
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5
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o
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ith
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s
[
2
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r
ain
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ed
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o
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et
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eit
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w
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s
:
th
e
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t
h
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e
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o
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y
:
∑
(
)
(
3
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th
e
ca
lcu
latio
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o
f
t
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e
Gi
n
i i
n
d
ex
:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
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J
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Do
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2
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3
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p
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ased
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ates
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t
cla
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le
[
2
2
]
.
I
n
th
e
s
i
m
p
lest
ca
s
e,
t
h
e
eq
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tio
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o
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d
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o
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b
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s
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ase
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ia
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w
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=1
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ai
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e
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t
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ay
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n
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r
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t
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i
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(
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)
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t
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t
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t
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a
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V
M
[
2
3
]
.
On
e
o
f
t
h
e
m
ai
n
in
d
icato
r
s
o
f
th
e
clas
s
i
f
ier
t
h
at
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i
ll
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lo
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u
s
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ev
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ate
it
s
e
f
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c
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h
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cu
r
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F1
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r
e
[
2
4
]
.
T
h
is
in
d
icato
r
d
ep
en
d
s
o
n
th
e
class
if
icatio
n
r
es
u
lts
o
f
t
h
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test
d
ataset:
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P
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m
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g
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a
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m
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1
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1
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3.
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te
[
2
5
]
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f
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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2
6
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.
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u
r
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4
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m
es
s
ag
e
is
r
ec
eiv
e
d
b
y
t
h
e
g
ate
w
a
y
,
a
co
r
r
esp
o
n
d
in
g
f
ea
t
u
r
e
v
ec
to
r
is
ex
tr
ac
ted
.
W
e
co
n
s
id
er
ed
t
h
e
f
o
llo
w
i
n
g
tr
a
f
f
ic
p
ar
a
m
eter
s
:
th
e
d
ela
y
b
et
w
ee
n
m
e
s
s
a
g
e
s
,
th
e
p
a
y
lo
ad
s
ize,
an
d
th
e
n
u
m
b
er
o
f
s
u
b
s
cr
ib
e
r
s
to
th
e
to
p
ic.
T
h
e
f
u
ll
f
ea
tu
r
e
v
ec
to
r
is
s
h
o
w
n
in
T
ab
le
2
.
A
ll
m
e
s
s
a
g
e
p
ar
am
eter
s
ca
n
b
e
r
etr
iev
ed
wh
en
t
h
e
g
a
te
w
a
y
s
o
f
t
w
ar
e
i
s
m
o
d
if
ied
.
T
ab
le
2
.
Featu
r
e
v
ec
to
r
o
f
m
es
s
ag
e
attr
ib
u
tes
u
s
i
n
g
t
h
e
MQ
T
T
P
r
o
t
o
co
l
D
e
f
i
n
i
t
i
o
n
P
a
r
a
me
t
e
r
Ty
p
e
U
se
r
n
a
me
U
se
r
`
s n
a
me
S
t
r
i
n
g
C
l
i
e
n
t
_
I
D
D
e
v
i
c
e
i
d
e
n
t
i
f
i
e
r
S
t
r
i
n
g
I
P
_
a
d
d
r
e
ss
N
e
t
w
o
r
k
a
d
d
r
e
ss o
f
d
e
v
i
c
e
S
t
r
i
n
g
TL
S
_
e
n
a
b
l
e
U
sag
e
o
f
c
r
y
p
t
o
g
r
a
p
h
i
c
t
r
a
n
sf
o
r
mat
i
o
n
s
B
o
o
l
e
a
n
Q
o
S
Q
u
a
l
i
t
y
o
f
se
r
v
i
c
e
0
,
1
o
r
2
T
i
me
T
i
me
w
h
e
n
a
me
ssag
e
w
a
s re
g
i
st
e
r
e
d
a
t
t
h
e
g
a
t
e
w
a
y
Ms
P
a
y
l
o
a
d
_
si
z
e
P
a
y
l
o
a
d
si
z
e
o
f
me
ssag
r
B
y
t
e
S
u
b
s
c
r
i
b
e
r
s_
N
N
u
mb
e
r
o
f
su
b
scr
i
b
e
r
s
U
n
i
t
s
T
h
u
s
,
h
av
i
n
g
o
n
e
f
ea
t
u
r
e
v
ec
t
o
r
,
all
th
r
ee
clas
s
if
ier
s
ca
n
o
p
er
ate
in
p
ar
allel,
as
s
h
o
w
n
i
n
Fig
u
r
e
2
,
u
s
i
n
g
th
e
ap
p
r
o
p
r
iate
la
b
el
(
User
n
a
m
e,
C
lie
n
t_
I
D,
o
r
I
P
_
ad
d
r
ess
)
.
I
n
o
r
d
er
to
r
e
d
u
ce
th
e
n
u
m
b
er
o
f
f
a
u
lt
p
o
s
itiv
e
a
n
d
f
a
u
lt
n
e
g
ati
v
e
er
r
o
r
s
,
an
av
er
ag
e
f
ea
tu
r
e
v
ec
to
r
o
f
m
e
s
s
a
g
es
r
ec
ei
v
ed
o
v
er
a
ti
m
e
in
ter
v
al
w
a
s
s
u
b
m
itted
to
t
h
e
cla
s
s
i
f
ier
s
.
T
o
d
ef
in
e
th
e
m
o
s
t a
p
p
r
o
p
r
iate
ti
m
e
i
n
ter
v
al
w
a
s
o
n
e
o
f
t
h
e
m
ain
p
r
o
b
le
m
s
in
th
is
r
esear
ch
.
W
e
s
elec
ted
th
e
f
o
ll
o
w
i
n
g
s
et
o
f
ti
m
e
in
ter
v
al
s
v
a
r
y
in
g
i
n
th
e
r
an
g
e
(
2
0
;
2
0
0
0
0
)
MS:
2
0
,
5
0
,
1
0
0
,
2
5
0
,
5
0
0
,
1
0
0
0
,
1
5
0
0
,
2
0
0
0
,
5
0
0
0
,
1
0
0
0
0
,
1
5
0
0
0
,
2
0
0
0
0
.
3.
1.
M
o
delin
g
t
est
a
nd
t
ra
in
ing
da
t
a
s
et
W
e
s
i
m
u
lated
n
et
w
o
r
k
tr
af
f
ic
b
asi
n
g
o
n
th
e
f
o
llo
w
i
n
g
p
ar
am
eter
s
:
m
e
s
s
a
g
e
f
r
eq
u
e
n
c
y
,
p
a
y
lo
ad
s
ize,
n
u
m
b
er
o
f
s
u
b
s
cr
ib
er
s
,
Qo
S
v
alu
e,
a
n
d
u
s
e
o
f
cr
y
p
to
g
r
ap
h
ic
tr
an
s
f
o
r
m
a
tio
n
s
.
T
w
o
s
ce
n
ar
i
o
s
h
a
v
e
co
n
s
id
er
ed
f
o
r
leg
al
tr
af
f
ic.
I
n
th
e
f
ir
s
t
o
n
e,
th
e
d
elay
i
n
ter
v
al
b
et
w
ee
n
m
es
s
ag
e
s
b
elo
n
g
ed
to
a
r
an
g
e
o
f
(
0
;
5
0
0
)
MS,
th
e
s
ize
o
f
t
h
e
p
a
y
lo
ad
(
1
;
8
0
)
B
y
te
s
,
an
d
t
h
e
n
u
m
b
er
o
f
s
u
b
s
cr
ib
er
s
(
1
;
5
)
u
n
its
.
T
h
e
s
ec
o
n
d
s
ce
n
ar
io
w
as
in
tr
o
d
u
ce
d
w
it
h
a
lo
n
g
d
ela
y
t
i
m
e
b
et
w
ee
n
m
e
s
s
a
g
es
(
0
;
5
0
0
0
)
MS,
w
ith
t
h
e
p
a
y
lo
ad
s
ize
(
0
;
8
0
0
)
B
y
tes,
an
d
th
e
n
u
m
b
er
o
f
s
u
b
s
cr
ib
er
s
in
t
h
e
r
an
g
e
o
f
(
1
; 1
0
)
.
A
b
n
o
r
m
al
tr
a
f
f
ic
w
a
s
p
r
ese
n
t
ed
w
i
th
a
m
i
n
i
m
u
m
d
ela
y
b
et
w
ee
n
m
es
s
a
g
es
(
0
M
S)
an
d
/
o
r
a
lar
g
e
p
ay
lo
ad
s
ize
(
6
0
;
8
0
)
K
b
y
te
s
an
d
/o
r
m
an
y
s
u
b
s
cr
ib
er
s
(
7
5
;
1
0
0
)
.
T
h
u
s
,
tr
af
f
ic
w
a
s
r
ec
o
g
n
ized
as
b
ein
g
ab
n
o
r
m
al
if
at
least
o
n
e
p
ar
am
eter
co
r
r
esp
o
n
d
ed
to
th
e
ab
o
v
e
ch
ar
ac
ter
is
tic
s
.
Fo
r
ea
ch
s
ce
n
ar
io
o
f
leg
iti
m
at
e
tr
af
f
ic
a
co
r
r
esp
o
n
d
in
g
ab
n
o
r
m
al
tr
a
f
f
ic
h
as
b
ee
n
s
i
m
u
lated
.
T
h
e
test
d
ata
s
et
h
as
b
ee
n
s
i
m
u
lated
in
a
s
i
m
ilar
w
a
y
b
u
t ti
m
e
i
n
ter
v
a
ls
f
o
r
p
ar
a
m
eter
s
f
l
u
ctu
a
tio
n
f
o
r
leg
al
a
n
d
ab
n
o
r
m
al
tr
af
f
ic
h
av
e
b
ee
n
ex
ten
d
ed
.
4.
RE
SU
L
T
S AN
D
AN
AL
Y
SI
S
I
n
o
r
d
er
to
d
eter
m
i
n
e
th
e
m
o
s
t
s
u
itab
le
cla
s
s
i
f
icatio
n
m
e
th
o
d
o
n
th
e
s
a
m
e
test
a
n
d
tr
ain
i
n
g
d
ata,
w
e
ca
lcu
lated
F1
-
s
co
r
e
v
al
u
es
f
o
r
tr
af
f
ic
e
v
al
u
atio
n
at
d
i
f
f
er
en
t
ti
m
e
i
n
ter
v
al
s
.
Up
o
n
co
m
p
let
io
n
o
f
th
e
ex
p
er
i
m
e
n
t,
w
e
o
b
tain
ed
t
h
e
f
o
llo
w
i
n
g
r
es
u
lts
.
Fo
r
t
h
e
f
ir
s
t
s
ce
n
ar
io
o
f
le
g
al
tr
a
f
f
ic
a
s
s
h
o
w
n
i
n
Fi
g
u
r
e
5
(
a)
i
n
th
e
ar
ea
f
r
o
m
5
0
MS
to
1
0
0
0
MS,
w
e
m
a
n
ag
ed
to
ac
h
ie
v
e
a
v
al
u
e
o
f
F1
-
s
co
r
e
g
r
ea
t
er
th
a
n
0
.
8
f
o
r
al
l
class
i
f
ier
s
.
C
o
m
p
ar
ed
clas
s
i
f
i
er
s
c
an
b
e
s
p
lit
i
n
to
t
w
o
g
r
o
u
p
s
.
T
h
e
f
ir
s
t
g
r
o
u
p
i
s
t
h
e
r
an
d
o
m
f
o
r
est
alg
o
r
it
h
m
an
d
th
e
s
u
p
p
o
r
t
v
ec
to
r
m
ac
h
i
n
e
w
it
h
R
B
F,
w
h
er
e
t
h
e
v
al
u
e
o
f
th
e
F1
-
s
co
r
e
b
eg
in
s
to
d
ec
r
ea
s
e
r
ap
id
ly
w
h
en
th
e
ti
m
e
i
n
ter
v
a
l
in
cr
ea
s
es
b
y
m
o
r
e
t
h
a
n
1
0
0
0
MS.
T
h
e
s
ec
o
n
d
g
r
o
u
p
,
co
n
s
is
t
i
n
g
o
f
t
h
e
r
e
m
ai
n
in
g
cla
s
s
i
f
ier
s
,
h
ad
F1
-
s
co
r
e
v
al
u
e
clo
s
e
to
0
.
9
w
ith
t
h
e
s
a
m
e
in
ter
v
al
v
al
u
es.
Fo
r
s
m
all
in
ter
v
al
s
(
n
o
t
ex
ce
ed
in
g
1
0
0
MS)
,
th
e
b
est
r
esu
l
ts
h
a
v
e
b
ee
n
o
b
s
er
v
ed
f
o
r
th
e
s
u
p
p
o
r
t
v
ec
to
r
m
ac
h
in
e
w
it
h
a
li
n
ea
r
k
er
n
el
f
u
n
ct
io
n
,
th
e
s
u
p
p
o
r
t
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
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lec
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n
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&
C
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m
p
Sci
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N:
2502
-
4752
Do
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tta
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J.
G
r
a
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a
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,
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c
u
rit
y
f
o
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T
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in
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s:
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ro
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mm
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1
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5
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]
S
.
S
ica
ri,
e
t
a
l
.
,
“
S
e
c
u
rit
y
,
p
riv
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tru
st
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tern
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s:
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ro
a
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]
M
.
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,
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:
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[4
]
E.
N.
V
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li
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o
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.
e
t
a
l.
,
“
Im
p
ro
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iffere
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]
M
.
A
.
Kh
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S
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lah
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b
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,
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t
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re
Ge
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ra
ti
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mp
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ter
S
y
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ms
,
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2
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.
[6
]
M
.
F
re
y
,
e
t
a
l.
,
“
S
e
c
u
rit
y
f
o
r
th
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In
d
u
strial
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:
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[
7
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O
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Q
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U
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[8
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B.
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if
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P
a
tri
c
i
u
V
.
,
“
M
i
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ti
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p
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Pro
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in
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fer
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fi
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l
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telli
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ter
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a
l.
,
”
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-
Ba
Io
T
:
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tw
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a
se
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te
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ti
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tn
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sin
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,
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Per
v
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siv
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ti
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l
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1
3
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p
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t
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0
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3
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7
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3
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0
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N.
Ko
ro
n
i
o
ti
s,
e
t
a
l.
,
“
T
o
w
a
rd
s
t
h
e
d
e
v
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lo
p
m
e
n
t
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f
r
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a
li
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b
o
tn
e
t
d
a
tas
e
t
in
th
e
in
tern
e
t
o
f
th
in
g
s
f
o
r
n
e
tw
o
rk
f
o
re
n
sic
a
n
a
l
y
ti
c
s:
Bo
t
-
Io
T
d
a
tas
e
t”,
Fu
tu
re
Ge
n
e
ra
ti
o
n
Co
mp
u
ter
S
y
ste
ms
1
0
0
,
p
p
.
7
7
9
-
7
9
6
,
2
0
1
9
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tt
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f
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re
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2
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4
1
.
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1
]
V
-
D.
P
h
a
m
,
e
t
a
l.
,
“
Re
s
e
a
rc
h
o
f
P
r
o
to
c
o
ls
o
f
In
tera
c
ti
o
n
o
f
th
e
In
tern
e
t
o
f
T
h
in
g
s
o
n
th
e
Ba
sis
o
f
th
e
L
a
b
o
ra
to
ry
Be
n
c
h
”
,
T
e
lec
o
m IT
,
v
o
l.
4
,
n
o
.
1
p
p
.
5
5
-
6
7
,
2
0
1
6
(i
n
R
u
ss
ian
).
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2
]
R.
Do
lg
u
sh
e
v
,
e
t
a
l.
,
“
A
n
Ov
e
rv
ie
w
o
f
P
o
ss
ib
le T
e
stin
g
Ty
p
e
s an
d
M
e
th
o
d
s f
o
r
th
e
In
tern
e
t
o
f
T
h
in
g
s”
,
T
e
lec
o
m IT
.
v
o
l.
4
,
n
o
.
2
p
p
.
1
-
1
1
,
2
0
1
6
(in
Ru
ss
ian
).
[1
3
]
P
.
F
e
h
re
n
b
a
c
h
,
“
M
e
ss
a
g
in
g
Qu
e
u
e
s
in
t
h
e
Io
T
u
n
d
e
r
p
re
ss
u
re
”
,
Co
mp
u
ta
t
io
n
a
l
S
c
ien
c
e
a
n
d
Its
Ap
p
li
c
a
ti
o
n
s
–
ICCS
A
.
2
0
1
8
.
p
p
.
1
-
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.
URL
:
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tt
p
s://
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lo
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it
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.
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4
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B.
M
ish
ra
,
“
P
e
rf
o
rm
a
n
c
e
Ev
a
lu
a
ti
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f
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QT
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e
r
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rv
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,
L
e
c
tu
re
No
tes
in
C
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ter
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,
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p
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tt
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3
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9
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3
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4
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.
[1
5
]
M
.
Ha
n
d
o
sa
,
D.
G
ra
c
a
n
in
,
“
P
e
rf
o
rm
a
n
c
e
e
v
a
lu
a
ti
o
n
o
f
m
q
tt
-
b
a
se
d
in
tern
e
t
o
f
th
in
g
s
s
y
ste
m
s”
,
In
Pro
c
e
e
d
in
g
s
o
f
th
e
2
0
1
7
W
in
ter
S
imu
l
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ti
o
n
C
o
n
f
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n
c
e
,
p
p
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tt
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:/
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.
[1
6
]
S
.
N.
F
ird
o
u
s,
e
t
a
l.
,
“
M
o
d
e
ll
in
g
a
n
d
Ev
a
lu
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ti
o
n
o
f
M
a
li
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s
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tt
a
c
k
s
a
g
a
in
st
th
e
Io
T
M
QT
T
P
ro
to
c
o
l”,
I
n
Pro
c
e
e
d
in
g
s
2
0
1
7
IEE
E
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
In
ter
n
e
t
o
f
T
h
in
g
s
(
iT
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in
g
s)
a
n
d
IE
EE
Gr
e
e
n
Co
mp
u
t
in
g
a
n
d
Co
mm
u
n
ica
ti
o
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s
(
Gr
e
e
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Co
m)
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n
d
IEE
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Cy
b
e
r,
P
h
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sic
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